PURPOSE: A classical twin study was performed to establish the relative importance of genes and environment in cortical cataract. METHODS: Five hundred six pairs of unselected female twin volunteers (226 monozygotic and 280 dizygotic) with a mean age of 62 years (range, 49-79 years) were examined. Cortical cataract was assessed using the slit-lamp-based Oxford Clinical Cataract Classification and Grading System (clinical grading) and the Wilmer Automated Grading System, which analyzed digital retroillumination images of subjects' lenses (digital grading). The worse eye categorized score for each individual was used in maximum likelihood path modeling of the correlations within twin pairs. These correlations were used to determine the underlying liability to cortical cataract. RESULTS: Prevalence of significant cortical cataract (>/=5% of lens area) was similar in monozygotic and dizygotic twins, occurring in 19.4% and 20.6% with the clinical grading system and 24% and 23% using the digital grading system, respectively. Modeling suggested liability to cortical cataract is explained by additive and dominant genes, individual environment, and age. Estimates of the broad sense heritability of cortical cataract were 58% (95% confidence interval [CI], 51%-64%) for the clinical grading system and 53% (95% CI, 45%-60%) for the digital system. Dominant genes were estimated to contribute to 38% (95% CI, 1%-64%) of the genetic effect with the clinical grading and 53% (95% CI, 28%-60%) with the digital grading. Individual environment explained 26% and 37% and age 16% and 11% of cortical cataract variance in clinical and digital gradings, respectively. CONCLUSIONS: Genetic effects are important in the development of cortical cataract and involve the action of dominant genes.
PURPOSE: A classical twin study was performed to establish the relative importance of genes and environment in cortical cataract. METHODS: Five hundred six pairs of unselected female twin volunteers (226 monozygotic and 280 dizygotic) with a mean age of 62 years (range, 49-79 years) were examined. Cortical cataract was assessed using the slit-lamp-based Oxford Clinical Cataract Classification and Grading System (clinical grading) and the Wilmer Automated Grading System, which analyzed digital retroillumination images of subjects' lenses (digital grading). The worse eye categorized score for each individual was used in maximum likelihood path modeling of the correlations within twin pairs. These correlations were used to determine the underlying liability to cortical cataract. RESULTS: Prevalence of significant cortical cataract (>/=5% of lens area) was similar in monozygotic and dizygotic twins, occurring in 19.4% and 20.6% with the clinical grading system and 24% and 23% using the digital grading system, respectively. Modeling suggested liability to cortical cataract is explained by additive and dominant genes, individual environment, and age. Estimates of the broad sense heritability of cortical cataract were 58% (95% confidence interval [CI], 51%-64%) for the clinical grading system and 53% (95% CI, 45%-60%) for the digital system. Dominant genes were estimated to contribute to 38% (95% CI, 1%-64%) of the genetic effect with the clinical grading and 53% (95% CI, 28%-60%) with the digital grading. Individual environment explained 26% and 37% and age 16% and 11% of cortical cataract variance in clinical and digital gradings, respectively. CONCLUSIONS: Genetic effects are important in the development of cortical cataract and involve the action of dominant genes.
Authors: Smriti A Agrawal; Deepti Anand; Archana D Siddam; Atul Kakrana; Soma Dash; David A Scheiblin; Christine A Dang; Anne M Terrell; Stephanie M Waters; Abhyudai Singh; Hozumi Motohashi; Masayuki Yamamoto; Salil A Lachke Journal: Hum Genet Date: 2015-04-21 Impact factor: 4.132
Authors: Aniket Mishra; Seyhan Yazar; Alex W Hewitt; Jenny A Mountain; Wei Ang; Craig E Pennell; Nicholas G Martin; Grant W Montgomery; Christopher J Hammond; Terri L Young; Stuart Macgregor; David A Mackey Journal: Invest Ophthalmol Vis Sci Date: 2012-10-11 Impact factor: 4.799
Authors: Sarah A Pendergrass; Shefali S Verma; Emily R Holzinger; Carrie B Moore; John Wallace; Scott M Dudek; Wayne Huggins; Terrie Kitchner; Carol Waudby; Richard Berg; Catherine A McCarty; Marylyn D Ritchie Journal: Pac Symp Biocomput Date: 2013
Authors: Gyungah Jun; Hong Guo; Barbara E K Klein; Ronald Klein; Jie Jin Wang; Paul Mitchell; Hui Miao; Kristine E Lee; Tripti Joshi; Matthias Buck; Preeti Chugha; David Bardenstein; Alison P Klein; Joan E Bailey-Wilson; Xiaohua Gong; Tim D Spector; Toby Andrew; Christopher J Hammond; Robert C Elston; Sudha K Iyengar; Bingcheng Wang Journal: PLoS Genet Date: 2009-07-31 Impact factor: 5.917