6 research outputs found

    Time spent outdoors partly accounts for the effect of education on myopia

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    Purpose: The purpose of this study was to investigate if education contributes to the risk of myopia because educational activities typically occur indoors or because of other factors, such as prolonged near viewing. Methods: This was a two-sample Mendelian randomization study. Participants were from the UK Biobank, Avon Longitudinal Study of Parents and Children, and Generation R. Genetic variants associated with years spent in education or time spent outdoors were used as instrumental variables. The main outcome measures were: (1) spherical equivalent refractive error attained by adulthood, and (2) risk of an early age-of-onset of spectacle wear (EAOSW), defined as an age-of-onset of 15 years or below. Results: Time spent outdoors was found to have a small genetic component (heritability 9.8%) that tracked from childhood to adulthood. A polygenic score for time outdoors was associated with children's time outdoors; a polygenic score for years spent in education was inversely associated with children's time outdoors. Accounting for the relationship between time spent outdoors and myopia in a multivariable Mendelian randomization analysis reduced the size of the causal effect of more years in education on myopia to −0.17 diopters (D) per additional year of formal education (95% confidence interval [CI] = −0.32 to −0.01) compared with the estimate from a univariable Mendelian randomization analysis of −0.27 D per year (95% CI = −0.41 to −0.13). Comparable results were obtained for the outcome EAOSW. Conclusions: Accounting for the effects of time outdoors reduced the estimated causal effect of education on myopia by 40%. These results suggest about half of the relationship between education and myopia may be mediated by children not being outdoors during schooling

    A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration.

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    BackgroundHigh myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ -6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER.MethodsThe PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression.FindingsIn independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17-21%), 2% (1-3%), 8% (7-10%) and 6% (3-9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75-0.81), 0.58 (0.53-0.64), 0.71 (0.69-0.74) and 0.67 (0.62-0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92-1.24).InterpretationPerformance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted for.FundingSupported by the Welsh Government and Fight for Sight (24WG201)

    A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

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    Background High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ −6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. Methods The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. Findings In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17–21%), 2% (1–3%), 8% (7–10%) and 6% (3–9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75–0.81), 0.58 (0.53–0.64), 0.71 (0.69–0.74) and 0.67 (0.62–0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92–1.24). Interpretation Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted fo

    A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

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    Background: High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ −6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. Methods: The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. Findings: In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17–21%), 2% (1–3%), 8% (7–10%) and 6% (3–9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75–0.81), 0.58 (0.53–0.64), 0.71 (0.69–0.74) and 0.67 (0.62–0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92–1.24). Interpretation: Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted for. Funding: Supported by the Welsh Government and Fight for Sight ( 24WG201).</p
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