ObjectivesTo determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education.DesignBidirectional, two sample mendelian randomisation study.SettingPublically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively.Participants67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error.Main outcome measuresMendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error.ResultsConventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of −0.18 dioptres/y (95% confidence interval −0.19 to −0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: −0.27 dioptres/y (−0.37 to −0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error −0.008 y/dioptre, 95% confidence interval −0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least −1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates.ConclusionsThis study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability.

; for the UK Biobank Eye and Vision Consortium IMPORTANCE Myopia is a leading cause of untreatable visual impairment and is increasing in prevalence worldwide. Interventions for slowing childhood myopia progression have shown success in randomized clinical trials; hence, there is a need to identify which children would benefit most from treatment intervention. OBJECTIVES To examine whether genetic information alone can identify children at risk of myopia development and whether including a child's genetic predisposition to educational attainment is associated with improved genetic prediction of the risk of myopia. DESIGN, SETTING, AND PARTICIPANTS Meta-analysis of 3 genome-wide association studies (GWAS) including a total of 711 984 individuals. These were a published GWAS for educational attainment and 2 GWAS for refractive error in the UK Biobank, which is a multisite cohort study that recruited participants between January 2006 and October 2010. A polygenic risk score was applied in a population-based validation sample examined between September 1998 and September 2000 (Avon Longitudinal Study of Parents and Children [ALSPAC] mothers). Data analysis was performed from February 2018 to May 2019. MAIN OUTCOMES AND MEASURES The primary outcome was the area under the receiver operating characteristic curve (AUROC) in analyses for predicting myopia, using noncycloplegic autorefraction measurements for myopia severity levels of less than or equal to −0.75 diopter (D) (any), less than or equal to −3.00 D (moderate), or less than or equal to −5.00 D (high). The predictor variable was a polygenic risk score (PRS) derived from genome-wide association study data for refractive error (n = 95 619), age of onset of spectacle wear (n = 287 448), and educational attainment (n = 328 917). RESULTS A total of 383 067 adults aged 40 to 69 years from the UK Biobank were included in the new GWAS analyses. The PRS was evaluated in 1516 adults aged 24 to 51 years from the ALSPAC mothers cohort. The PRS had an AUROC of 0.67 (95% CI, 0.65-0.70) for myopia, 0.75 (95% CI, 0.70-0.79) for moderate myopia, and 0.73 (95% CI, 0.66-0.80) for high myopia. Inclusion in the PRS of information associated with genetic predisposition to educational attainment marginally improved the AUROC for myopia (AUROC, 0.674 vs 0.668; P = .02), but not those for moderate and high myopia. Individuals with a PRS in the top 10% were at 6.1-fold higher risk (95% CI, 3.4-10.9) of high myopia. CONCLUSIONS AND RELEVANCE A personalized medicine approach may be feasible for detecting very young children at risk of myopia. However, accuracy must improve further to merit uptake in clinical practice; currently, cycloplegic autorefraction remains a better indicator of myopia risk (AUROC, 0.87).

Purpose Cross-sectional and longitudinal studies have consistently reported an association between education and myopia. However, conventional observational studies are at risk of bias due to confounding by factors such as socioeconomic position and parental educational attainment. The current study aimed to estimate the causal effect of education on refractive error using regression discontinuity analysis. Methods Regression discontinuity analysis was applied to assess the influence on refractive error of the raising of the school leaving age (ROSLA) from 15 to 16 years introduced in England and Wales in 1972. For comparison, a conventional ordinary least squares (OLS) analysis was performed. The analysis sample comprised 21,548 UK Biobank participants born in a nine-year interval centered on September 1957, the date of birth of those first affected by ROSLA. Results In OLS analysis, the ROSLA 1972 reform was associated with a −0.29 D (95% confidence interval [CI]: −0.36 to −0.21, P < 0.001) more negative refractive error. In other words, the refractive error of the study sample became more negative by −0.29 D during the transition from a minimum school leaving age of 15 to 16 years of age. Regression discontinuity analysis estimated the causal effect of the ROSLA 1972 reform on refractive error as −0.77 D (95% CI: −1.53 to −0.02, P = 0.04). Conclusions Additional compulsory schooling due to the ROSLA 1972 reform was associated with a more negative refractive error, providing additional support for a causal relationship between education and myopia.

Strabismus refers to an abnormal alignment of the eyes leading to the loss of central binocular vision. Concomitant strabismus occurs when the angle of deviation is constant in all positions of gaze and often manifests in early childhood when it is considered to be a neurodevelopmental disorder of the visual system. As such, it is inherited as a complex genetic trait, affecting 2-4% of the population. A genome-wide association study (GWAS) for self-reported strabismus (1345 cases and 65,349 controls from UK Biobank) revealed a single genome-wide significant locus on chromosome 17q25. Approximately 20 variants across the NPLOC4-TSPAN10-PDE6G gene cluster and in almost perfect linkage disequilibrium (LD) were most strongly associated (lead variant: rs75078292, OR = 1.26, p = 2.24E−08). A recessive model provided a better fit to the data than an additive model. Association with strabismus was independent of refractive error, and the degree of association with strabismus was minimally attenuated after adjustment for amblyopia. The association with strabismus was replicated in an independent cohort of clinician-diagnosed children aged 7 years old (116 cases and 5084 controls; OR = 1.85, p = 0.009). The associated variants included 2 strong candidate causal variants predicted to have functional effects: rs6420484, which substitutes tyrosine for a conserved cysteine (C177Y) in the TSPAN10 gene, and a 4-bp deletion variant, rs397693108, predicted to cause a frameshift in TSPAN10. The population-attributable risk for the locus was approximately 8.4%, indicating an important role in conferring susceptibility to strabismus.

Purpose To test for causality with regard to the association between blood pressure (BP) and intraocular pressure (IOP) and glaucoma. Methods Single nucleotide polymorphisms (SNPs) associated with BP were identified in a genome-wide association study (GWAS) meta-analysis of 526,001 participants of European ancestry. These SNPs were used to assess the BP versus IOP relationship in a distinct sample ( n = 70,832) whose corneal-compensated IOP (IOPcc) was measured. To evaluate the BP versus primary open-angle glaucoma (POAG) relationship, additional Mendelian randomization (MR) analyses were conducted using published GWAS summary statistics. Results Observational analysis revealed a linear relationship between BP traits and IOPcc, with a +0.28 mm Hg increase in IOPcc per 10-mm Hg increase in systolic BP (95% confidence interval [CI], 0.26–0.29); for diastolic blood pressure (DBP) and pulse pressure (PP), these estimates were +0.41 mm Hg and +0.36 mm Hg, respectively. An inverse-variance weighted MR analysis did not support a causal relationship, as the estimated causal effect was +0.01 mm Hg IOPcc per 10-mm Hg increase in systolic blood pressure (SBP); +0.13 mm Hg IOPcc per 10-mm Hg increase in DBP; and +0.02 mm Hg IOPcc per 10-mm Hg increase in PP (all P > 0.05). With regard to the risk of POAG, MR analyse yielded causal effect estimate of odds ratio = 0.98 (95% CI, 0.92–1.04) per 10-mm Hg increase in SBP. Neither DBP nor PP demonstrated evidence of a causal effect on POAG. Conclusions A range of different MR analysis methods provided evidence, in general, that the causal effect of BP on IOP (and POAG) was modest, or even zero. However, interpretation was complicated by SNPs associated with BP potentially having pleiotropic effects on IOP.

Purpose Randomised controlled trials (RCTs) allow reliable causal inferences to be drawn regarding the effectiveness of specific interventions. However, they are expensive to carry out, and not all exposure‐outcome relationships can be tested in an RCT framework: for example, it would be unethical to deliberately expose participants to a putative risk factor, or the time‐scale involved may be prohibitive. Mendelian randomisation (MR) has been proposed as an alternative approach for drawing causal inferences, with the major advantage that the method can often be applied to existing, cross‐sectional study datasets. Therefore, results from an MR study can be obtained much more quickly and cheaply than through an RCT. Recent findings The validity of causal inferences from an MR study are dependent on two key assumptions, neither of which can be tested fully. Nevertheless, several approaches have been proposed in the last 3 years that either highlight questionable results, or provide valid causal inference if the necessary assumptions are met only in part. Compared to certain other areas of clinical practice, the ophthalmic research community has been slow to adopt MR. Summary An MR study cannot match an RCT in its strength of evidence for a claim of causality. However, MR still has much to offer. In some circumstances, an MR study can provide causal insight into research questions that cannot be addressed by an RCT, while more generally, an MR study can be used to evaluate the supporting evidence before deciding to embark on a lengthy and costly RCT.

BackgroundPathological myopia is one of the leading causes of blindness globally. Lower birth weight (BW) within the normal range has been reported to increase the risk of myopia, although findings conflict. We sought to estimate the causal effect of BW on refractive error using Mendelian randomisation (MR), under the assumption of a linear relationship.MethodsGenetic variants associated with BW were identified from meta-analysis of a genome-wide association study (GWAS) for self-reported BW in 162 039 UK Biobank participants and a published Early Growth Genetics (EGG) consortium GWAS (n=26 836). We performed a one-sample MR analysis in 39 658 unrelated, adult UK Biobank participants (independent of the GWAS sample) using an allele score for BW as instrumental variable. A two-sample MR sensitivity analysis and conventional ordinary least squares (OLS) regression analyses were also undertaken.ResultsIn OLS analysis, BW showed a small, positive association with refractive error: +0.04 D per SD increase in BW (95% CI 0.02 to 0.07; p=0.002). The one-sample MR-estimated causal effect of BW on refractive error was higher, at +0.28 D per SD increase in BW (95% CI 0.05 to 0.52, p=0.02). A two-sample MR analysis provided similar causal effect estimates, with minimal evidence of directional pleiotropy.ConclusionsOur study suggests lower BW within the normal range is causally associated with a more myopic refractive error. However, the impact of the causal effect was modest (range 1.00 D covering approximately 95% of the population).

Citation: Pozarickij A, Enthoven CA, Ghorbani Mojarrad N, et al. Evidence that emmetropization buffers against both genetic and environmental risk factors for myopia. Invest Ophthalmol Vis Sci. 2020;61(2):41. https://doi.org/10.1167/iovs.61.2.41 PURPOSE.To test the hypothesis that emmetropization buffers against genetic and environmental risk factors for myopia by investigating whether risk factor effect sizes vary depending on children's position in the refractive error distribution. METHODS. Refractive error was assessed in participants from two birth cohorts: AvonLongitudinal Study of Parents and Children (ALSPAC) (noncycloplegic autorefraction) and Generation R (cycloplegic autorefraction). A genetic risk score for myopia was calculated from genotypes at 146 loci. Time spent reading, time outdoors, and parental myopia were ascertained from parent-completed questionnaires. Risk factors were coded as binary variables (0 = low, 1 = high risk). Associations between refractive error and each risk factor were estimated using either ordinary least squares (OLS) regression or quantile regression. RESULTS.Quantile regression: effects associated with all risk factors (genetic risk, parental myopia, high time spent reading, low time outdoors) were larger for children in the extremes of the refractive error distribution than for emmetropes and low ametropes in the center of the distribution. For example, the effect associated with having a myopic parent for children in quantile 0.05 vs. 0.50 was as follows: ALSPAC: age 15, -1.19 D (95% CI -1.75 to -0.63) vs. -0.13 D (-0.19 to -0.06), P = 0.001; Generation R: age 9, -1.31 D (-1.80 to -0.82) vs. -0.19 D (-0.26 to -0.11), P < 0.001. Effect sizes for OLS regression were intermediate to those for quantiles 0.05 and 0.50. CONCLUSIONS.Risk factors for myopia were associated with much larger effects in children in the extremes of the refractive error distribution, providing indirect evidence that emmetropization buffers against both genetic and environmental risk factors.