Seyedeh Maryam Zekavat1, Sayuri Sekimitsu2, Yixuan Ye3, Vineet Raghu4, Hongyu Zhao5, Tobias Elze6, Ayellet V Segrè6, Janey L Wiggs6, Pradeep Natarajan7, Lucian Del Priore8, Nazlee Zebardast6, Jay C Wang9. 1. Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, Connecticut; Computational Biology & Bioinformatics Program, Yale University, New Haven, Connecticut; Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. 2. Tufts University School of Medicine, Boston, Massachusetts. 3. Computational Biology & Bioinformatics Program, Yale University, New Haven, Connecticut. 4. Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. 5. Computational Biology & Bioinformatics Program, Yale University, New Haven, Connecticut; School of Public Health, Yale University, New Haven, Connecticut. 6. Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts. 7. Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, Massachusetts; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. 8. Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, Connecticut. 9. Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, Connecticut; Northern California Retina Vitreous Associates, Mountain View, California. Electronic address: jay.wang@yale.edu.
Abstract
PURPOSE: Despite widespread use of OCT, an early-stage imaging biomarker for age-related macular degeneration (AMD) has not been identified. Pathophysiologically, the timing of drusen accumulation in relationship to photoreceptor degeneration in AMD remains unclear, as are the inherited genetic variants contributing to these processes. Herein, we jointly analyzed OCT, electronic health record data, and genomic data to characterize the time sequence of changes in retinal layer thicknesses in AMD, as well as epidemiologic and genetic associations between retinal layer thicknesses and AMD. DESIGN: Cohort study. PARTICIPANTS: Forty-four thousand eight hundred twenty-three individuals from the UK Biobank (enrollment age range, 40-70 years; 54% women; median follow-up, 10 years). METHODS: The Topcon Advanced Boundary Segmentation algorithm was used for retinal layer segmentation. We associated 9 retinal layer thicknesses with prevalent AMD (present at enrollment) in a logistic regression model and with incident AMD (diagnosed after enrollment) in a Cox proportional hazards model. Next, we associated AMD-associated genetic alleles, individually and as a polygenic risk score (PRS), with retinal layer thicknesses. All analyses were adjusted for age, age-squared (age2), sex, smoking status, and principal components of ancestry. MAIN OUTCOME MEASURES: Prevalent and incident AMD. RESULTS: Photoreceptor segment (PS) thinning was observed throughout the lifespan of individuals analyzed, whereas retinal pigment epithelium (RPE) and Bruch's membrane (BM) complex thickening started after 57 years of age. Each standard deviation (SD) of PS thinning and RPE-BM complex thickening was associated with incident AMD (PS: hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.23-1.47; P = 3.7 × 10-11; RPE-BM complex: HR, 1.14; 95% CI, 1.06-1.22; P = 0.00024). The AMD PRS was associated with PS thinning (β, -0.21 SD per twofold genetically increased risk of AMD; 95% CI, -0.23 to -0.19; P = 2.8 × 10-74), and its association with RPE-BM complex was U-shaped (thinning with AMD PRS less than the 92nd percentile and thickening with AMD PRS more than the 92nd percentile). The loci with strongest support for genetic correlation were AMD risk-raising variants Complement Factor H (CFH):rs570618-T, CFH:rs10922109-C, and Age-Related Maculopathy Susceptibility 2 (ARMS2)/High-Temperature Requirement Serine Protease 1 (HTRA1):rs3750846-C on PS thinning and SYN3/Tissue Inhibitor of Metalloprotease 3 (TIMP3):rs5754227-T on RPE-BM complex thickening. CONCLUSIONS: Epidemiologically, PS thinning precedes RPE-BM complex thickening by decades and is the retinal layer most strongly predictive of future AMD risk. Genetically, AMD risk variants are associated with decreased PS thickness. Overall, these findings support PS thinning as an early-stage biomarker for future AMD development.
PURPOSE: Despite widespread use of OCT, an early-stage imaging biomarker for age-related macular degeneration (AMD) has not been identified. Pathophysiologically, the timing of drusen accumulation in relationship to photoreceptor degeneration in AMD remains unclear, as are the inherited genetic variants contributing to these processes. Herein, we jointly analyzed OCT, electronic health record data, and genomic data to characterize the time sequence of changes in retinal layer thicknesses in AMD, as well as epidemiologic and genetic associations between retinal layer thicknesses and AMD. DESIGN: Cohort study. PARTICIPANTS: Forty-four thousand eight hundred twenty-three individuals from the UK Biobank (enrollment age range, 40-70 years; 54% women; median follow-up, 10 years). METHODS: The Topcon Advanced Boundary Segmentation algorithm was used for retinal layer segmentation. We associated 9 retinal layer thicknesses with prevalent AMD (present at enrollment) in a logistic regression model and with incident AMD (diagnosed after enrollment) in a Cox proportional hazards model. Next, we associated AMD-associated genetic alleles, individually and as a polygenic risk score (PRS), with retinal layer thicknesses. All analyses were adjusted for age, age-squared (age2), sex, smoking status, and principal components of ancestry. MAIN OUTCOME MEASURES: Prevalent and incident AMD. RESULTS: Photoreceptor segment (PS) thinning was observed throughout the lifespan of individuals analyzed, whereas retinal pigment epithelium (RPE) and Bruch's membrane (BM) complex thickening started after 57 years of age. Each standard deviation (SD) of PS thinning and RPE-BM complex thickening was associated with incident AMD (PS: hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.23-1.47; P = 3.7 × 10-11; RPE-BM complex: HR, 1.14; 95% CI, 1.06-1.22; P = 0.00024). The AMD PRS was associated with PS thinning (β, -0.21 SD per twofold genetically increased risk of AMD; 95% CI, -0.23 to -0.19; P = 2.8 × 10-74), and its association with RPE-BM complex was U-shaped (thinning with AMD PRS less than the 92nd percentile and thickening with AMD PRS more than the 92nd percentile). The loci with strongest support for genetic correlation were AMD risk-raising variants Complement Factor H (CFH):rs570618-T, CFH:rs10922109-C, and Age-Related Maculopathy Susceptibility 2 (ARMS2)/High-Temperature Requirement Serine Protease 1 (HTRA1):rs3750846-C on PS thinning and SYN3/Tissue Inhibitor of Metalloprotease 3 (TIMP3):rs5754227-T on RPE-BM complex thickening. CONCLUSIONS: Epidemiologically, PS thinning precedes RPE-BM complex thickening by decades and is the retinal layer most strongly predictive of future AMD risk. Genetically, AMD risk variants are associated with decreased PS thickness. Overall, these findings support PS thinning as an early-stage biomarker for future AMD development.
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