Genome-wide association studies for corneal and refractive astigmatism in UK Biobank demonstrate a shared role for myopia susceptibility loci

Shah, Rupal L.; Guggenheim, Jeremy A.

doi:10.1007/s00439-018-1942-8

Cited by 53 publications

(44 citation statements)

References 75 publications

(108 reference statements)

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“…288 289 Corneal astigmatism and age 290 Corneal astigmatism decreases significantly with age by an average 0.06D in both eyes per decade even 291 after controlling for weight and height (Table 3.2). This is contrary to what is reported by [34] namely 292 that the level of corneal astigmatism is relatively constant across age. As reported by Shah et al in a 293 previous UKBB analysis [34], we did confirm the stronger association between age and refractive 294 (cylindrical) astigmatism in right eye (B=0.011 (0.010 to 0.011), P<.001) and left eye (B=0.010 (0.09 to 295 0.010), P<0.001) ( Figure S3.a).…”

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“…This is contrary to what is reported by [34] namely 292 that the level of corneal astigmatism is relatively constant across age. As reported by Shah et al in a 293 previous UKBB analysis [34], we did confirm the stronger association between age and refractive 294 (cylindrical) astigmatism in right eye (B=0.011 (0.010 to 0.011), P<.001) and left eye (B=0.010 (0.09 to 295 0.010), P<0.001) ( Figure S3.a). The fact that refractive astigmatism increases with age but that corneal 296 astigmatism decreases with age suggest that lenticular astigmatism may be driving the increase in 297 refractive astigmatism, possibly due to the onset of presbyopia.…”

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Frequency and Distribution of Corneal Astigmatism and Keratometry Features: Methodology and Findings of the UK Biobank Study

Pontikos

Chua

Foster

et al. 2019

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Purpose:32 To describe corneal astigmatism in the UK Biobank population, to look for associations with other 33 biometric variables and socio-demographic factors, and to report the proportion with abnormal 34 keratometry and irregular astigmatism suggestive of pathological corneal ectasias such as keratoconus.35 Methods:36 Cross-sectional data were obtained from UK Biobank (www.ukbiobank.ac.uk/). A subsample of 107,452 37 participants from UK communities had undergone an enhanced ophthalmic examination including 38 autorefractor keratometry (Tomey RC 5000, Tomey Corp., Nagoya, Japan). After quality control and 39 applying relevant exclusions, data on corneal astigmatism on 83,751 participants was available for 40 analysis. Potential associations were tested through univariable regression and significant parameters 41 carried forward for multivariable analysis. 42Results:43 In a univariable analysis, the characteristics significantly protective against corneal astigmatism were 44 gender (male), older age, darker skin colour and increased alcohol intake (all p<0.001). The parameters 45 significantly associated with increased corneal astigmatism were older age at completion of full time 46 education, use of UV protection and lower corrected visual acuity. After inclusion in the multivariable 47 analysis, age, gender, age at completion of full time education, corrected visual acuity and skin colour 48 remained significant (all p<0.001). Increased corneal astigmatism was also found to be significantly 49 associated with amblyopia or strabismus. No individuals with abnormal keratometry or irregular 50 astigmatism were reported. 51 Conclusions:52 This analysis of associations with astigmatism in a large cohort of volunteers confirms previous 53 associations including adverse associations with younger age and female gender, and identified novel 54 associations including darker skin colour and frequency of alcohol intake. The highest risk group for 55 corneal astigmatism were younger females of lighter skin colour, having completed full time education 3 56 later, with higher logMAR corrected visual acuity. We also confirmed that corneal astigmatism is a high 57 risk factor for amblyopia and strabismus. Finally since no cases of keratoconus were identified, this 58 would suggest that simple keratometry indices may not be sufficient for population screening of 59 keratoconus. 60 Introduction 61 Uncorrected refractive error is the leading cause of moderate to severe visual impairment in all age 62 groups globally (101.2 million individuals in 2010), and the second commonest cause of avoidable 63 blindness in children after cataract (6.8 million individuals in 2010) [1][2]. Refractive error (ametropia), is 64 a significant public health burden, frequently associated with worse visual acuity and higher risk of 65 developing amblyopia (lazy-eye). Corneal astigmatism is a leading cause of refractive error in children 66 and a significant increase in myopia as well as astigmatism has been reported in the Singaporean 67 population...

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Frequency and Distribution of Corneal Astigmatism and Keratometry Features: Methodology and Findings of the UK Biobank Study

Pontikos

Chua

Foster

et al. 2019

Preprint

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“…The online version of this article (https ://doi.org/10.1007/s0043 8-020-01666 -w) contains supplementary material, which is available to authorized users. h SNP 2 = 0.35-0.39% (Guggenheim et al 2015;Shah et al 2018). Genome-wide association studies (GWAS) have identified approximately 150 genetic variants associated with refractive error, which together explain approximately 4-6% of the inter-individual variation (Kiefer et al 2013;Verhoeven et al 2013;Tedja et al 2018).…”

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Non-additive (dominance) effects of genetic variants associated with refractive error and myopia

2020

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Genome-wide association studies (GWAS) have revealed that the genetic contribution to certain complex diseases is welldescribed by Fisher's infinitesimal model in which a vast number of polymorphisms each confer a small effect. Under Fisher's model, variants have additive effects both across loci and within loci. However, the latter assumption is at odds with the common observation of dominant or recessive rare alleles responsible for monogenic disorders. Here, we searched for evidence of non-additive (dominant or recessive) effects for GWAS variants known to confer susceptibility to the highly heritable quantitative trait, refractive error. Of 146 GWAS variants examined in a discovery sample of 228,423 individuals whose refractive error phenotype was inferred from their age-of-onset of spectacle wear, only 8 had even nominal evidence (p < 0.05) of non-additive effects. In a replication sample of 73,577 individuals who underwent direct assessment of refractive error, 1 of these 8 variants had robust independent evidence of non-additive effects (rs7829127 within ZMAT4, p = 4.76E−05) while a further 2 had suggestive evidence (rs35337422 in RD3L, p = 7.21E−03 and rs12193446 in LAMA2, p = 2.57E−02). Accounting for non-additive effects had minimal impact on the accuracy of a polygenic risk score for refractive error (R 2 = 6.04% vs. 6.01%). Our findings demonstrate that very few GWAS variants for refractive error show evidence of a departure from an additive mode of action and that accounting for non-additive risk variants offers little scope to improve the accuracy of polygenic risk scores for myopia.

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“…To identify genes associated with the development of refractive errors in humans among the genes whose expression correlated with refractive eye development in mice, human homologs of candidate mouse genes were examined for association with refractive error in the international genome-wide association study (GWAS) of refractive error carried out by the Consortium for Refractive Error and Myopia (CREAM) [54] and the UK Biobank Eye and Vision consortium sample [71] using the Multi-marker Analysis of GenoMic Annotation (MAGMA) [72]. Human homologs of candidate mouse genes were obtained from Ensembl BioMart and were mapped according to gene definitions in the NCBI Entrez Gene database.…”

Section: Identification Of Genes Associated With Refractive Error In mentioning

confidence: 99%

Analysis of genetic networks regulating refractive eye development in collaborative cross progenitor strain mice reveals new genes and pathways underlying human myopia

Tkatchenko

Shah

Nagasaki

2019

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Background: Population studies suggest that genetic factors play an important role in refractive error development; however, the precise role of genetic background and the composition of the signaling pathways underlying refractive eye development remain poorly understood.Methods: Here, we analyzed normal refractive development and susceptibility to formdeprivation myopia in the eight progenitor mouse strains of the Collaborative Cross (CC). We used RNA-seq to analyze gene expression in the retinae of these mice and reconstruct genetic networks and signaling pathways underlying refractive eye development. We also utilized genome-wide gene-based association analysis to identify mouse genes and pathways associated with myopia in humans. Results: Genetic background strongly influenced both baseline refractive development and susceptibility to environmentally-induced myopia. Baseline refractive errors ranged from -21.2 diopters (D) in 129S1/svlmj mice to +22.0 D in CAST/EiJ mice and represented a continuous distribution typical of a quantitative genetic trait. The extent of induced form-deprivation myopia ranged from -5.6 D in NZO/HILtJ mice to -20.0 D in CAST/EiJ mice and also followed a continuous distribution. Whole-genome (RNA-seq) gene expression profiling in retinae from CC progenitor strains identified genes whose expression level correlated with either baseline refractive error or susceptibility to myopia. Expression levels of 2,302 genes correlated with the baseline refractive state of the eye, whereas 1,917 genes correlated with susceptibility to induced myopia. Genome-wide gene-based association analysis in the CREAM and UK Biobank human Page 3 of 47cohorts revealed that 985 of the above genes were associated with myopia in humans, including 847 genes which were implicated in the development of human myopia for the first time.Although the gene sets controlling baseline refractive development and those regulating susceptibility to myopia overlapped, these two processes appeared to be controlled by largely distinct sets of genes. Conclusions: Comparison with data for other animal models of myopia revealed that the genes identified in this study comprise a well-defined set of retinal signaling pathways, which are highly conserved across different vertebrate species. These results identify major signaling pathways involved in refractive eye development and provide attractive targets for the development of anti-myopia drugs. BackgroundMyopia is the most common ocular disorder worldwide [1]. The prevalence of myopia in the U.S. has increased from 25% to ~48% in the last 40 years [2][3][4]. The worldwide prevalence of myopia is predicted to increase from the current 25% to 50% in the next three decades [5], while the prevalence already exceeds 80% in several parts of Asia [6,7]. Myopia often leads to serious blinding complications such as myopic maculopathy, retinal floaters, chorioretinal atrophy, retinoschisis, retinal tears, retinal detachment, and myopic macular degeneration [8][9][10][11][12][13][14][15][16]...

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Genome-wide association studies for corneal and refractive astigmatism in UK Biobank demonstrate a shared role for myopia susceptibility loci

Cited by 53 publications

References 75 publications

Frequency and Distribution of Corneal Astigmatism and Keratometry Features: Methodology and Findings of the UK Biobank Study

Frequency and Distribution of Corneal Astigmatism and Keratometry Features: Methodology and Findings of the UK Biobank Study

Non-additive (dominance) effects of genetic variants associated with refractive error and myopia

Analysis of genetic networks regulating refractive eye development in collaborative cross progenitor strain mice reveals new genes and pathways underlying human myopia

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