Education interacts with genetic variants near GJD2, RBFOX1, LAMA2, KCNQ5 and LRRC4C to confer susceptibility to myopia

Abstract

Myopia most often develops during school age, with the highest incidence in countries with intensive education systems. Interactions between genetic variants and educational exposure are hypothesized to confer susceptibility to myopia, but few such interactions have been identified. Here, we aimed to identify genetic variants that interact with education level to confer susceptibility to myopia. Two groups of unrelated participants of European ancestry from UK Biobank were studied. A ‘Stage-I’ sample of 88,334 participants whose refractive error (avMSE) was measured by autorefraction and a ‘Stage-II’ sample of 252,838 participants who self-reported their age-of-onset of spectacle wear (AOSW) but who did not undergo autorefraction. Genetic variants were prioritized via a 2-step screening process in the Stage-I sample: Step 1 was a genome-wide association study for avMSE; Step 2 was a variance heterogeneity analysis for avMSE. Genotype-by-education interaction tests were performed in the Stage-II sample, with University education coded as a binary exposure. On average, participants were 58 years-old and left full-time education when they were 18 years-old; 35% reported University level education. The 2-step screening strategy in the Stage-I sample prioritized 25 genetic variants (GWAS P < 1e-04; variance heterogeneity P < 5e-05). In the Stage-II sample, 19 of the 25 (76%) genetic variants demonstrated evidence of variance heterogeneity, suggesting the majority were true positives. Five genetic variants located near GJD2, RBFOX1, LAMA2, KCNQ5 and LRRC4C had evidence of a genotype-by-education interaction in the Stage-II sample (P < 0.002) and consistent evidence of a genotype-by-education interaction in the Stage-I sample. For all 5 variants, University-level education was associated with an increased effect of the risk allele. In this cohort, additional years of education were associated with an enhanced effect of genetic variants that have roles including axon guidance and the development of neuronal synapses and neural circuits.

Association between whole-grain intake and myopia in chinese children: a cross-sectional epidemiological study

“…Josh Wallman pointed out that the effect could possibly as well be explained if myopic parents, who are more likely to be wealthier and better educated, create more myopigenic environments [ 28 ]. Recently, Guggenheim has also suggested that genetic effects explain only part of the impact of parental myopia [ 29 ]. Currently, hundreds of genetic loci have been identified for refractive error and myopia, and risk variants mostly carry low risk but are highly prevalent in the general population.…”

Gene–environment interaction in myopia

“…It has been widely acknowledged that the discovery of interaction effects is much more difficult than finding genetic or environmental marginal effects 67 . Previously published results have seldom been replicated 12–14,19,22,23,25,26,28,31,35 . To the best of our knowledge, an interaction between GJD2 (rs524952) and near‐work burdens has been identified by two separate studies from different ethnicities 13,23 .…”

“…A recent study applied a two‐stage approach and found five variants near GJD2, FBFOX1, LAMA2, KCNQ5 and LRRC4C that could interact with educational level and the risk effects of these variants increased with additional years of education 26 …”

“…In addition, prioritising variance quantitative trait loci for interaction detection might be an additional way to improve statistical power and have better replication than GWAS loci 52 . Clark and colleagues 26 have already applied this method and investigated several SNPs that could interact with education. Further, Zhang and Belsky 53 suggested that gene selection must consider the assumptions of gene–environment (diathesis stress or differential susceptibility), different assumptions and the number of genes corresponding to different selection strategies.…”

“…A recent study applied a two-stage approach and found five variants near GJD2, FBFOX1, LAMA2, KCNQ5 and LRRC4C that could interact with educational level and the risk effects of these variants increased with additional years of education. 26 However, there was no evidence that environmental factors except for the near-work burden could interact with genetic markers, although time spent outdoors is another pivotal factor that could influence myopia onset. It has been shown that greater outdoor exposure slows the myopic shift and axial elongation only in children who were not yet myopic; however, the intervention became ineffective in children who were already myopic.…”