TY - JOUR
T1 - Bivariate analysis of age-related macular degeneration progression using genetic risk scores
AU - Ding, Ying
AU - Liu, Yi
AU - Yan, Qi
AU - Fritsche, Lars G.
AU - Cook, Richard J.
AU - Clemons, Traci
AU - Ratnapriya, Rinki
AU - Klein, Michael L.
AU - Abecasis, Gonçalo R.
AU - Swaroop, Anand
AU - Chew, Emily Y.
AU - Weeks, Daniel E.
AU - Chen, Wei
N1 - Funding Information:
We thank the participants in the AREDS and AREDS2 studies, who made this study possible, and the International Age-Related Macular Degeneration (AMD) Genomics Consortium for generating the genetic data and performing the quality check. This research was supported by the National Institutes of Health (EY024226 to W.C., Y.D., D.E.W., and Q.Y., EY022005 to G.R.A. and L.G.F., and EY021532 to M.L.K.), Intramural Research Program of the National Eye Institute (to A.S., E.Y.C., and R.P.), and RPB (Research to Prevent Blindness) unrestricted departmental grant (to M.L.K.). D.E.W. is a coinventor on licensed patents held by the University of Pittsburgh for the chromosome 10q26 PLEHA1 and ARMS2 loci for AMD.
Publisher Copyright:
© 2017 by the Genetics Society of America.
PY - 2017/5
Y1 - 2017/5
N2 - Age-related macular degeneration (AMD) is a leading cause of blindness in the developed world. While many AMD susceptibility variants have been identified, their influence on AMD progression has not been elucidated. Using data from two large clinical trials, Age-Related Eye Disease Study (AREDS) and AREDS2, we evaluated the effects of 34 known risk variants on disease progression. In doing so, we calculated the eye-level time-to-late AMD and modeled them using a bivariate survival analysis approach, appropriately accounting for between-eye correlation. We then derived a genetic risk score (GRS) based on these 34 risk variants, and analyzed its effect on AMD progression. Finally, we used the AREDS data to fit prediction models of progression based on demographic and environmental factors, eye-level AMD severity scores and the GRS and tested the models using the AREDS2 cohort. We observed that GRS was significantly associated with AMD progression in both cohorts, with a stronger effect in AREDS than in AREDS2 (AREDS: hazard ratio (HR) = 1.34, P = 1.6 × 10-22; AREDS2: HR = 1.11, P = 2.1 × 10-4). For prediction of AMD progression, addition of GRS to the demographic/environmental risk factors considerably improved the prediction performance. However, when the baseline eye-level severity scores were included as the predictors, any other risk factors including the GRS only provided small additional predictive power. Our model for predicting the disease progression risk demonstrated satisfactory performance in both cohorts, and we recommend its use with baseline AMD severity scores plus baseline age, education level, and smoking status, either with or without GRS.
AB - Age-related macular degeneration (AMD) is a leading cause of blindness in the developed world. While many AMD susceptibility variants have been identified, their influence on AMD progression has not been elucidated. Using data from two large clinical trials, Age-Related Eye Disease Study (AREDS) and AREDS2, we evaluated the effects of 34 known risk variants on disease progression. In doing so, we calculated the eye-level time-to-late AMD and modeled them using a bivariate survival analysis approach, appropriately accounting for between-eye correlation. We then derived a genetic risk score (GRS) based on these 34 risk variants, and analyzed its effect on AMD progression. Finally, we used the AREDS data to fit prediction models of progression based on demographic and environmental factors, eye-level AMD severity scores and the GRS and tested the models using the AREDS2 cohort. We observed that GRS was significantly associated with AMD progression in both cohorts, with a stronger effect in AREDS than in AREDS2 (AREDS: hazard ratio (HR) = 1.34, P = 1.6 × 10-22; AREDS2: HR = 1.11, P = 2.1 × 10-4). For prediction of AMD progression, addition of GRS to the demographic/environmental risk factors considerably improved the prediction performance. However, when the baseline eye-level severity scores were included as the predictors, any other risk factors including the GRS only provided small additional predictive power. Our model for predicting the disease progression risk demonstrated satisfactory performance in both cohorts, and we recommend its use with baseline AMD severity scores plus baseline age, education level, and smoking status, either with or without GRS.
KW - AMD progression
KW - AREDS
KW - Bivariate time-to-event
KW - Genetic risk score
KW - Risk prediction
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U2 - 10.1534/genetics.116.196998
DO - 10.1534/genetics.116.196998
M3 - Article
C2 - 28341650
AN - SCOPUS:85020735746
SN - 0016-6731
VL - 206
SP - 119
EP - 133
JO - Genetics
JF - Genetics
IS - 1
ER -