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Zekavat SM, Jorshery SD, Shweikh Y, Horn K, Rauscher FG, Sekimitsu S, Kayoma S, Ye Y, Raghu V, Zhao H, Ghassemi M, Elze T, Segrè AV, Wiggs JL, Scholz M, Priore LD, Wang JC, Natarajan P, Zebardast N. Insights into human health from phenome- and genome-wide analyses of UK Biobank retinal optical coherence tomography phenotypes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.16.23290063. [PMID: 37292770 PMCID: PMC10246137 DOI: 10.1101/2023.05.16.23290063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The human retina is a complex multi-layered tissue which offers a unique window into systemic health and disease. Optical coherence tomography (OCT) is widely used in eye care and allows the non-invasive, rapid capture of retinal measurements in exquisite detail. We conducted genome- and phenome-wide analyses of retinal layer thicknesses using macular OCT images from 44,823 UK Biobank participants. We performed phenome-wide association analyses, associating retinal thicknesses with 1,866 incident ICD-based conditions (median 10-year follow-up) and 88 quantitative traits and blood biomarkers. We performed genome-wide association analyses, identifying inherited genetic markers which influence the retina, and replicated our associations among 6,313 individuals from the LIFE-Adult Study. And lastly, we performed comparative association of phenome- and genome- wide associations to identify putative causal links between systemic conditions, retinal layer thicknesses, and ocular disease. Independent associations with incident mortality were detected for photoreceptor thinning and ganglion cell complex thinning. Significant phenotypic associations were detected between retinal layer thinning and ocular, neuropsychiatric, cardiometabolic and pulmonary conditions. Genome-wide association of retinal layer thicknesses yielded 259 loci. Consistency between epidemiologic and genetic associations suggested putative causal links between thinning of the retinal nerve fiber layer with glaucoma, photoreceptor segment with AMD, as well as poor cardiometabolic and pulmonary function with PS thinning, among other findings. In conclusion, retinal layer thinning predicts risk of future ocular and systemic disease. Furthermore, systemic cardio-metabolic-pulmonary conditions promote retinal thinning. Retinal imaging biomarkers, integrated into electronic health records, may inform risk prediction and potential therapeutic strategies.
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Affiliation(s)
- Seyedeh Maryam Zekavat
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Saman Doroodgar Jorshery
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Departments of Computer Science/Medicine, University of Toronto, Toronto, Canada
- Vector Institute for Artificial Intelligence, Toronto, ON, Canada
- Department of Computer Science and Electrical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yusrah Shweikh
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Katrin Horn
- Institute for Medical Informatics, Statistics and Epidemiology University of Leipzig, Germany and Leipzig Research Centre for Civilization Diseases (LIFE), Leipzig University, Leipzig, Germany
| | - Franziska G. Rauscher
- Institute for Medical Informatics, Statistics and Epidemiology University of Leipzig, Germany and Leipzig Research Centre for Civilization Diseases (LIFE), Leipzig University, Leipzig, Germany
| | | | - Satoshi Kayoma
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yixuan Ye
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
| | - Vineet Raghu
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hongyu Zhao
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
- School of Public Health, Yale University, New Haven, CT, USA
| | - Marzyeh Ghassemi
- Departments of Computer Science/Medicine, University of Toronto, Toronto, Canada
- Vector Institute for Artificial Intelligence, Toronto, ON, Canada
- Department of Computer Science and Electrical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Tobias Elze
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Ayellet V. Segrè
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Janey L. Wiggs
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology University of Leipzig, Germany and Leipzig Research Centre for Civilization Diseases (LIFE), Leipzig University, Leipzig, Germany
| | - Lucian Del Priore
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA
| | - Jay C. Wang
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT, USA
- Northern California Retina Vitreous Associates, Mountain View, CA
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nazlee Zebardast
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Langlo CS, Trotter A, Reddi HV, Schilter KF, Tyler RC, Udani R, Neitz M, Carroll J, Connor TB. Long-term retinal imaging of a case of suspected congenital rubella infection. Am J Ophthalmol Case Rep 2022; 25:101241. [PMID: 34977425 PMCID: PMC8688893 DOI: 10.1016/j.ajoc.2021.101241] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 07/16/2021] [Accepted: 12/06/2021] [Indexed: 11/18/2022] Open
Abstract
Purpose Many retinal disorders present with pigmentary retinopathy, most of which are progressive conditions. Here we present over nine years of follow up on a case of stable pigmentary retinopathy that is suspected to stem from a congenital rubella infection. Parafoveal cone photoreceptors were tracked through this period to gain insight into photoreceptor disruption in this pigmentary retinopathy. Methods The patient was examined at 8 visits spanning a total of 111 months. Examination at baseline included clinical fundus examination, full-field electroretinography (ERG), kinetic visual field assessment (Goldmann), and best corrected visual acuity; all of these except ERG were repeated at follow up visits. Imaging was performed with fundus photography, spectral-domain optical coherence tomography (SD-OCT) and confocal adaptive optics scanning light ophthalmoscopy (AOSLO). For the latter four time points AOSLO imaging also included split-detector imaging. Results There were no defects in hearing or cardiac health found in this patient. There were minimal visual deficits found at baseline, with mild rod suppression on ERG; best corrected visual acuity was 20/25 OD and 20/20 OS at baseline, which was stable throughout the follow-up period. Retinal thickness as measured by OCT was within the normal range, though foveal hypoplasia was present and outer nuclear layer thickness was slightly below the normal range at all time points. Cone density was relatively stable throughout the follow-up period. A number of cones were non-reflective when observed with confocal AOSLO imaging and density was markedly lower than expected values (foveal cone density was 43,782 cones/mm2 on average). Genetic analysis revealed no causative variations explaining the phenotype. Conclusions and Importance This patient appears to have a stable pigmentary retinopathy. This case is likely due to a congenital insult, rather than progressive retinal disease. This finding of stability agrees with other reports of rubella pigmentary retinopathy. Imaging with AOSLO enabled observation of two notable phenotypic features. First is the observation of dark cones, which are seen in many retinal disorders including color vision defects and degenerative retinal disease. Second, the cone density is well below what is expected – this is especially interesting as this patient has near-normal visual acuity despite this greatly decreased number of normally-waveguiding cones in the fovea.
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Affiliation(s)
- Christopher S Langlo
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Alana Trotter
- Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison, WI, USA
| | - Honey V Reddi
- Precision Medicine Laboratory, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Kala F Schilter
- Precision Medicine Laboratory, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Rebecca C Tyler
- Precision Medicine Laboratory, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Rupa Udani
- Precision Medicine Laboratory, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Maureen Neitz
- Department of Ophthalmology, University of Washington, Seattle, WA, USA
| | - Joseph Carroll
- Department of Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.,Department of Ophthalmology and Visual Sciences, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Thomas B Connor
- Department of Ophthalmology and Visual Sciences, Medical College of Wisconsin, Milwaukee, WI, USA
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