Carla Lanca1,2,3, Irfahan Kassam4,5, Karina Patasova6, Li-Lian Foo1,7,8, Jonathan Li9, Marcus Ang1,7,8, Quan V Hoang1,7,8,10, Yik-Ying Teo4, Pirro G Hysi6,11, Seang-Mei Saw1,4,8. 1. Singapore Eye Research Institute, Singapore. 2. Comprehensive Health Research Center (CHRC), Escola Nacional de Saúde Pública, Universidade Nova de Lisboa, Lisboa, Portugal. 3. Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL), Instituto Politécnico de Lisboa, Lisboa, Portugal. 4. Saw Swee Hock School of Public Health, National University of Singapore. 5. Life Sciences Institute, National University of Singapore. 6. Section of Ophthalmology, School of Life Course Sciences, King's College London, United Kingdom Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, UK. 7. Singapore National Eye Centre, Singapore. 8. Duke-NUS Medical School, Singapore. 9. Department of Ophthalmology, University of California San Francisco, San Francisco, CA, USA. 10. Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 11. UCL Great Ormond Street Hospital Institute of Child Health, University College London, UK.
Abstract
Purpose: The purpose of this study was to develop an Asian polygenic risk score (PRS) to predict high myopia (HM) in Chinese children in the Singapore Cohort of Risk factors for Myopia (SCORM) cohort. Methods: We included children followed from 6 to 11 years old until teenage years (12-18 years old). Cycloplegic autorefraction, ultrasound biometry, Illumina HumanHap 550, or 550 Duo Beadarrays, demographics, and environmental factors data were obtained. The PRS was generated from the Consortium for Refractive Error and Myopia genomewide association study (n = 542,934) and the Strabismus, Amblyopia, and Refractive Error in Singapore children Study (n = 500). The Growing Up in Singapore Towards healthy Outcomes Cohort study (n = 339) was the replication cohort. The outcome was teenage HM (≤ -5.00 D) with predictive performance assessed using the area under the curve (AUC). Results: Mean baseline age ± SD was 7.85 ± 0.84 (n = 1004) and 571 attended the teenage visit; 23.3% had HM. In multivariate analysis, the PRS was associated with a myopic spherical equivalent with an incremental R2 of 0.041 (95% confidence interval [CI] = 0.010, 0.073; P < 0.001). AUC for HM (0.77 [95% CI = 0.71-0.83]) performed better (P = 0.02) with the PRS compared with a model without (0.72 [95% CI = 0.65, 0.78]). Children at the top 25% PRS risk had a 2.34-fold-greater risk of HM (95% CI = 1.53, 3.55; P < 0.001). Conclusions: The new Asian PRS improved the predictive performance to detect children at risk of HM. Translational Relevance: Clinicians may use the PRS with other predictive factors to identify high risk children and guide interventions to reduce the risk of HM later in life.
Purpose: The purpose of this study was to develop an Asian polygenic risk score (PRS) to predict high myopia (HM) in Chinese children in the Singapore Cohort of Risk factors for Myopia (SCORM) cohort. Methods: We included children followed from 6 to 11 years old until teenage years (12-18 years old). Cycloplegic autorefraction, ultrasound biometry, Illumina HumanHap 550, or 550 Duo Beadarrays, demographics, and environmental factors data were obtained. The PRS was generated from the Consortium for Refractive Error and Myopia genomewide association study (n = 542,934) and the Strabismus, Amblyopia, and Refractive Error in Singapore children Study (n = 500). The Growing Up in Singapore Towards healthy Outcomes Cohort study (n = 339) was the replication cohort. The outcome was teenage HM (≤ -5.00 D) with predictive performance assessed using the area under the curve (AUC). Results: Mean baseline age ± SD was 7.85 ± 0.84 (n = 1004) and 571 attended the teenage visit; 23.3% had HM. In multivariate analysis, the PRS was associated with a myopic spherical equivalent with an incremental R2 of 0.041 (95% confidence interval [CI] = 0.010, 0.073; P < 0.001). AUC for HM (0.77 [95% CI = 0.71-0.83]) performed better (P = 0.02) with the PRS compared with a model without (0.72 [95% CI = 0.65, 0.78]). Children at the top 25% PRS risk had a 2.34-fold-greater risk of HM (95% CI = 1.53, 3.55; P < 0.001). Conclusions: The new Asian PRS improved the predictive performance to detect children at risk of HM. Translational Relevance: Clinicians may use the PRS with other predictive factors to identify high risk children and guide interventions to reduce the risk of HM later in life.