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Estimating the Genetic Contribution to Astigmatism and Myopia in the Mexican Population

Published online by Cambridge University Press:  16 October 2023

Talía V. Román-López
Affiliation:
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Brisa García-Vilchis
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Vanessa Murillo-Lechuga
Affiliation:
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Enrique Chiu-Han
Affiliation:
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Xanat López-Camaño
Affiliation:
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Oscar Aldana-Assad
Affiliation:
Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Santiago Diaz-Torres
Affiliation:
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
Ulises Caballero-Sánchez
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Ivett Ortega-Mora
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Diego Ramírez-González
Affiliation:
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Diego Zenteno
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Zaida Espinosa-Valdés
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Andrea Tapia-Atilano
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Sofía Pradel-Jiménez
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Miguel E. Rentería
Affiliation:
Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
Alejandra Medina-Rivera
Affiliation:
Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
Alejandra E. Ruiz-Contreras*
Affiliation:
Laboratorio de Neurogenómica Cognitiva, Unidad de Investigación en Psicobiología y Neurociencias, Coordinación de Psicobiología y Neurociencias, Facultad de Psicología, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México
Sarael Alcauter*
Affiliation:
Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
*
Corresponding authors: Alejandra E. Ruiz-Contreras; Email: aleruiz@unam.mx; Sarael Alcauter; Email: alcauter@inb.unam.mx
Corresponding authors: Alejandra E. Ruiz-Contreras; Email: aleruiz@unam.mx; Sarael Alcauter; Email: alcauter@inb.unam.mx

Abstract

Astigmatism and myopia are two common ocular refractive errors that can impact daily life, including learning and productivity. Current knowledge suggests that the etiology of these conditions is the result of a complex interplay between genetic and environmental factors. Studies in populations of European ancestry have demonstrated a higher concordance of refractive errors in monozygotic (MZ) twins compared to dizygotic (DZ) twins. However, there is a lack of studies on genetically informative samples of multi-ethnic ancestry. This study aimed to estimate the genetic contribution to astigmatism and myopia in the Mexican population. A sample of 1399 families, including 243 twin pairs and 1156 single twins, completed a medical questionnaire about their own and their co-twin’s diagnosis of astigmatism and myopia. Concordance rates for astigmatism and myopia were estimated, and heritability and genetic correlations were determined using a bivariate ACE Cholesky decomposition method, decomposed into A (additive genetic), C (shared environmental) and E (unique environmental) components. The results showed a higher concordance rate for astigmatism and myopia for MZ twins (.74 and .74, respectively) than for DZ twins (.50 and .55). The AE model, instead of the ACE model, best fitted the data. Based on this, heritability estimates were .81 for astigmatism and .81 for myopia, with a cross-trait genetic correlation of rA = .80, nonshared environmental correlation rE = .89, and a phenotypic correlation of rP = .80. These results are consistent with previous findings in other populations, providing evidence for a similar genetic architecture of these conditions in the multi-ethnic Mexican population.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Society for Twin Studies

Astigmatism and myopia are two prevalent ocular refractive errors that have become significant public health concerns globally (Baird et al., Reference Baird, Saw, Lanca, Guggenheim, Smith, Zhou, Matsui, Wu, Sankaridurg, Chia, Rosman, Lamoureux, Man and He2020; Hashemi et al., Reference Hashemi, Fotouhi, Yekta, Pakzad, Ostadimoghaddam and Khabazkhoob2017; Pascolini & Mariotti, Reference Pascolini and Mariotti2012). Astigmatism is characterized by unequal curvatures in the cornea or crystalline lens, leading to rotational asymmetries and blurry projections of light over the retina (Harb & Wildsoet, Reference Harb and Wildsoet2019; Harris, Reference Harris2000; Visnjić et al., Reference Visnjić, Zrinsćak, Barisić, Iveković, Laus and Mandić2012). Myopia, also known as nearsightedness, is caused by the light being focused in front of the retina instead of on it, leading to a blurred perception of distant objects (Harb & Wildsoet, Reference Harb and Wildsoet2019). The elongation of the eye and corneal modifications (e.g., keratoconus) can contribute to myopia (Baird et al., Reference Baird, Saw, Lanca, Guggenheim, Smith, Zhou, Matsui, Wu, Sankaridurg, Chia, Rosman, Lamoureux, Man and He2020).

The worldwide prevalence of myopia was estimated to be ∼33% by the World Health Organization in 2020, and a meta-analysis of global studies estimated a prevalence of 26.5% for myopia and 40.4% for astigmatism (Holden et al., Reference Holden, Fricke, Wilson, Jong, Naidoo, Sankaridurg, Wong, Naduvilath and Resnikoff2016). However, data varies greatly between regions and ethnic groups, with higher prevalence in some groups (Hashemi et al., Reference Hashemi, Fotouhi, Yekta, Pakzad, Ostadimoghaddam and Khabazkhoob2017; Rose et al., Reference Rose, Smith, Morgan and Mitchell2001). For example, in East and Southeast Asia, myopia is considered an epidemic among adults, with 80−90% suffering from it (Morgan et al., Reference Morgan, French, Ashby, Guo, Ding, He and Rose2018). In contrast, half of the European population suffer from some refraction error, with around 30% of myopia and 23% of astigmatism (Williams et al., Reference Williams, Verhoeven, Cumberland, Bertelsen, Wolfram, Buitendijk, Hofman, van Duijn, Vingerling, Kuijpers, Höhn, Mirshahi, Khawaja, Luben, Erke, von Hanno, Mahroo, Hogg, Gieger and Hammond2015). The comorbidity between astigmatism and myopia also varies among populations; for example, it has been estimated at 3.8% (3250/19,686) in the Albanian population (Kleves, Reference Kleves2021), but at 58% in American children (Fulton et al., Reference Fulton, Hansen and Petersen1982). Meanwhile, data from other regions, such as Latin America, is scarce. In Mexico, astigmatism and myopia have been recognized as common ocular problems (Secretaría de Salud, Reference de Salud2020). Specifically, in a sample of 676,856 Mexican patients (aged 6 to 90), myopia was the most common refractive error at 24.8%, while astigmatism was present in 13.5% of the sample (Gomez-Salazar et al., Reference Gomez-Salazar, Campos-Romero, Gomez-Campaña, Cruz-Zamudio, Chaidez-Felix, Leon-Sicairos, Velazquez-Roman, Flores-Villaseñor, Muro-Amador, Guadron-Llanos, Martinez-Garcia, Murillo-Llanes, Sanchez-Cuen, Llausas-Vargas, Alapizco-Castro, Irineo-Cabrales, Graue-Hernandez, Ramirez-Luquin and Canizalez-Roman2017). Studies of school-age children in urban areas showed a prevalence of 44% for bilateral myopia and 9.5% for astigmatism, while those in rural areas were estimated at 9.7% and 4.4% respectively (Garcia-Lievanos et al., Reference Garcia-Lievanos, Sanchez-Gonzalez, Espinosa-Cruz, Hernandez-Flores, Salmeron-Leal and Torres-Rodriguez2016). Refractive errors impact aspects of life such as education and employment (Kandel et al., Reference Kandel, Khadka, Goggin and Pesudovs2017); as such, the concern about these conditions is growing. They are predicted to affect over 50% of the world’s population by 2050 (Holden et al., Reference Holden, Fricke, Wilson, Jong, Naidoo, Sankaridurg, Wong, Naduvilath and Resnikoff2016); thus, evaluating the etiology of refractive errors is crucial.

Previous research suggests that both genetic and environmental factors play a role in the development of astigmatism and myopia (Baird et al., Reference Baird, Saw, Lanca, Guggenheim, Smith, Zhou, Matsui, Wu, Sankaridurg, Chia, Rosman, Lamoureux, Man and He2020; Gordon-Shaag et al., Reference Gordon-Shaag, Shneor, Doron, Levine and Ostrin2021; Read et al., Reference Read, Collins and Carney2007; Young et al., Reference Young, Metlapally and Shay2007). For instance, genomewide association studies (GWASs) have identified various risk polymorphisms for both conditions, including genes involved in eye growth, retinal proteins, corneal epithelium, neurotransmission, and retinoic acid metabolism (Harb & Wildsoet, Reference Harb and Wildsoet2019; Hysi et al., Reference Hysi, Young, Mackey, Andrew, Fernández-Medarde, Solouki, Hewitt, Macgregor, Vingerling, Li, Ikram, Fai, Sham, Manyes, Porteros, Lopes, Carbonaro, Fahy, Martin and Hammond2010; Kiefer et al., Reference Kiefer, Tung, Do, Hinds, Mountain, Francke and Eriksson2013; Lopes et al., Reference Lopes, Hysi, Verhoeven, Macgregor, Hewitt, Montgomery, Cumberland, Vingerling, Young, van Duijn, Oostra, Uitterlinden, Rahi, Mackey, Klaver and Hammond2013; Nakanishi et al., Reference Nakanishi, Yamada, Gotoh, Hayashi, Yamashiro, Shimada, Ohno-Matsui, Mochizuki, Saito, Iida, Matsuo, Tajima, Yoshimura and Matsuda2009; Shah, Li et al., Reference Shah, Li, Zhao, Tedja, Tideman, Khawaja, Fan, Yazar, Williams, Verhoeven, Xie, Wang, Hess, Nickels, Lackner, Pärssinen, Wedenoja, Biino, Concas, Uitterlinden and Bailey-Wilson2018; Wojciechowski, Reference Wojciechowski2011; Wojciechowski & Hysi, Reference Wojciechowski and Hysi2013). However, the genetic connection between astigmatism and myopia remains inconclusive, with some studies suggesting a shared genetic etiology (Pinazo-Durán et al., Reference Pinazo-Durán, Zanón-Moreno, García-Medina, Arévalo, Gallego-Pinazo and Nucci2016; Shah, Guggenheim et al., Reference Shah and Guggenheim2018; Young et al., Reference Young, Metlapally and Shay2007) and others considering them as different manifestations of refractive errors (Dirani et al., Reference Dirani, Islam, Shekar and Baird2008; Hammond et al., Reference Hammond, Snieder, Gilbert and Spector2001; Paget et al., Reference Paget, Julia, Vitezica, Soler, Malecaze and Calvas2008). Environmental factors, such as prolonged near-work activities, outdoor time, reduced sleep, education, muscle changes, and population density also seem to play a role (Demir et al., Reference Demir, Baskaran, Theagarayan, Gierow, Sankaridurg and Macedo2021; Harb & Wildsoet, Reference Harb and Wildsoet2019; Li et al., Reference Li, Wei, Le, Gawargious and Demer2019; Saad & El Bayoumy, Reference Saad and El Bayoumy2007; Wang et al., Reference Wang, Tong, Hao, Chen, Zhu, Huang, Li, Hu and Liu2021; Wojciechowski, Reference Wojciechowski2011; Xiong et al., Reference Xiong, Sankaridurg, Naduvilath, Zang, Zou, Zhu, Lv, He and Xu2017; Zhang et al., Reference Zhang, Li, Chen, Lee, Wu, Yang, Chen, Xu, Lam, Sharma, Griffiths, Gao and Congdon2010). For example, studies have suggested that more time spent in outdoor activities reduces the risk of developing myopia (Jin et al., Reference Jin, Hua, Jiang, Wu, Yang, Gao, Fang, Pei, Wang, Zhang, Tao and Tao2015; Xiong et al., Reference Xiong, Sankaridurg, Naduvilath, Zang, Zou, Zhu, Lv, He and Xu2017); meanwhile, near-work activities such as reading or the overuse of smartphones, which involve short viewing distance, force the eye to modify the optical convergences and increase eyelid pressure onto the cornea, resulting in increased risk of developing both myopia and astigmatism (Dutheil et al., Reference Dutheil, Oueslati, Delamarre, Castanon, Maurin, Chiambaretta, Baker, Ugbolue, Zak, Lakbar, Pereira and Navel2023; Leung et al., Reference Leung, Chan, Lam, Tong and Kee2020). Other studies have suggested that sociodemographic variables could be related to developing myopia, as this is more prevalent in urban and higher income populations compared to rural and lower income, which could be related in turn to near-work and outdoor activities (Ragot et al., Reference Ragot, Baraza and Clarke-Farr2020).

Twin studies are useful in evaluating the combined impact of genes and environment (Sahu & Prasuna, Reference Sahu and Prasuna2016). For example, a study in Norway showed higher concordance rates for astigmatism in monozygotic twins than in dizygotic twins, suggesting a genetic influence (Grjibovski et al., Reference Grjibovski, Magnus, Midelfart and Harris2006). The heritability of astigmatism was estimated to be over 60% in an Australian twin study (Dirani et al., Reference Dirani, Islam, Shekar and Baird2008). In addition, a Chinese twin study also found significant contributions from both genes and environment to myopia (C.-J. Chen et al., Reference Chen, Cohen and Diamond1985). However, the contribution of genes and environment in genetically admixed populations, such as the Mexican, is practically unknown. The Mexican population is largely underrepresented in genetic studies but has a high prevalence of refractive errors. This study aims to determine the concordance rates, heritability, and genetic cross-trait correlation of astigmatism and myopia in Mexican twins.

Methods

Sample

Data used for this study comes from the Mexican Twin Registry, TwinsMX (https://twinsmxofficial.unam.mx/; Leon-Apodaca et al., Reference Leon-Apodaca, Chiu-Han, Ortega-Mora, Román-López, Caballero-Sánchez, Aldana-Assad, Campos, Cuellar-Partida, Ruiz-Contreras, Alcauter, Rentería and Medina-Rivera2019), collected using the Research Electronic Data Capture (REDCap) platform, hosted at the National Laboratory of Advanced Scientific Visualization at the Universidad Nacional Autónoma de México (UNAM). All participants gave informed consent, and the study protocol was reviewed and approved by the Research Ethics Committee of the Institute of Neurobiology at UNAM.

At the time of data extraction (April 2022), TwinsMX included data for 2778 families. For this study, we selected subjects who completed the medical questionnaire and were aged 7 years or older (considering that the age to start school can vary between 6−7 years old in Mexico), resulting in a sample of N = 1887 families. Zygosity status was participant-reported; twin pairs whose reported zygosity did not match (e.g., one twin reported MZ and the co-twin reported DZ) were classified as indeterminate (Sánchez-Romera, Reference Sánchez-Romera2013) and were excluded (n = 9). Subjects from other multiple birth types (e.g., triplets or quadruplets) or who did not report the sex of their co-twin were also excluded. The final sample consisted of N = 1399 families. A family was defined for either a singleton or a pair of twins. In this study, 243 families with both twins being registered (i.e., 486 individuals) and 1156 families with only one registered twin were included in the final sample. The 1156 single twins reported information about their unregistered twin, and with this information we were able to analyze a sample of N = 2798 individuals (i.e., 486 + [1156*2]). Sociodemographic data, sex and age of the twins were also acquired.

Myopia and Astigmatism Participant-Reported Diagnosis

Twins answered a medical questionnaire where they were asked ‘Have you, your parents, siblings, or children ever suffered some of the following conditions?’, and tick boxes allowed participants to state which family members had presented with the condition. Among the possible answers, myopia and astigmatism were listed.

Statistical Analyses

Participants were split into two main groups, All MZ and All DZ, based on the self-reported zygosity. Additionally, each twin reported their sex and their twin’s sex. With that information, families were classified into five different subgroups depending on zygosity and sex as has been widely reported: MZ female (MZF), MZ male (MZM), DZ female (DZF), DZ male (DZM), and DZ opposite-sex (DZOS) (e.g., Grjibovski et al., Reference Grjibovski, Magnus, Midelfart and Harris2006; Hopper et al., Reference Hopper, Hannah, Macaskill and Mathews1990; Loat et al., Reference Loat, Galsworthy, Plomin and Craig2004; Vink & Boomsma, Reference Vink and Boomsma2011).

The participant-report diagnosis was used for families where both twins were part of the registry. For the families where only one of the twins was part of the registry (single twins), we considered the report about themselves and the report about their twin. To address the concern of reliability of a single twin reporting the diagnosis of the nonregistered co-twin, we adopted the following strategy: first, we analyzed the responses from the 243 twin pairs (both twins registered) and tested the consistency of their answers regarding their co-twin. That is, we compared the twins’ response about their co-twin, since in these 243 families we have data from both twins.

In addition, we estimated the concordance rate for the diagnoses (i.e., presence or absence of astigmatism and myopia, independently performed one from another) only for the 243 twin pairs, to assess whether the results obtained from the entire sample (i.e., 1399 families) were consistent.

Demographic analysis

We compared the distribution of sex and age between the MZ and DZ groups using an independent chi-square test (χ2). Additionally, we reported the prevalence of having at least one of the two conditions, that is, only myopia, only astigmatism, or both. We used an independent chi-square test to evaluate whether sex or zygosity distribution differed among the three groups.

Concordance rate test

We calculated probandwise concordance for both astigmatism and myopia following the model reported by McGue (Reference McGue1992), and calculated the respective confidence intervals for proportions for each group and subgroups of zygosity and sex. Due to the small sample size of some of the zygosity and sex subgroups, only the comparisons between concordance rates for All MZ and All DZ groups, without stratification by sex, were tested with the Likelihood Ratio Test. Only results with p < .05 were considered statistically significant.

Bivariate ACE Cholesky analysis

We performed the ACE Cholesky decomposition, which allows estimating the amount of variance of each phenotype, explained by the genetic contribution or heritability (A), the shared environmental contribution (C), and the unique environment (E). In addition, a multivariate design (in this case, a bivariate model) allows to estimate the covariation between myopia and astigmatism. For a detailed description of these analyses, see Zietsch et al. (Reference Zietsch, Kuja-Halkola, Walum and Verweij2014) and Posthuma (Reference Posthuma and Kim2009).

Briefly, the bivariate model assumes that latent variables have effects on the traits of interest (see Figure 1 for the path model). First, we consider the genetic contribution from two sets of genes (latent variables A1 and A2) by directly associating the first gene set over one trait (i.e., A1 over astigmatism) through a path (a11), and the second set of genes over the second trait (i.e., A2 acting over myopia) through a second path (a22). Second, the model takes into account the shared genes for astigmatism and myopia, which are modeled on the influence of A1 over the second trait, myopia (path a21). The effect of the set of genes A2 over the first trait (astigmatism) via a12 is not modeled to avoid redundancy; namely, it is assumed that if an overlapping of shared genes exists, these will be the same group of genes within A1 or A2 sets, then the path a21 is already reflecting the conjunction of shared genes. Additionally, it is relevant to notice that, in a Cholesky factorization, the lower triangular solution is mathematically equivalent to the upper triangular solution (see matrix a below). Similarly, the respective shared and nonshared environmental contributions are correspondingly modeled by C and E from paths.

Figure 1. Bivariate path modeling for astigmatism and myopia. Cholesky decomposition in latent variables: A (genetic contribution), C (shared environment influence), and E (residual or nonshared environmental influences). A1 represents the latent variable (i.e., the set of genes) that contributes to astigmatism (path a11) and myopia (path a21). A2 is the second latent variable (i.e., a second set of genes) affecting myopia. Also shown are the respective variables for shared and nonshared environmental contributions (C and E).

The corresponding matrix design of this bivariate path model is an n × n matrix, where n is the number of traits in the model, in this case, a 2 × 2 matrix a = $\left( {\matrix{ {{a_{11}}} & 0 \cr {{a_{21}}} & {{a_{22}}} \cr } } \right)$ . The total genetic contribution is estimated as the result of A = a*aT, given as a result A = $\left( {\matrix{ {a_{11}^2} & {{a_{11}}{a_{21}}} \cr {{a_{21}}{a_{11}}} & {a_{21}^2a_{22}^2} \cr } } \right)$ . The A(1,1) = a11 2 is the total genetic contribution (i.e., heritability) of the trait 1, A(2,2) = a2 21 + a2 22, is the total genetic contribution (i.e., heritability) of the trait 2. Meanwhile, the cross-trait, cross-twin genetic covariance is A(2,1) = a11a21. To estimate the genetic correlation between the traits of interest, astigmatism, and myopia, r A = ${\rm{\;}}{{{a_{11}}*{a_{21}}} \over {\sqrt {a_{11}^2} \;*\;\sqrt {\;\;a_{21}^2\; + \;a_{22}^2\;} \;}}$ . The variance and covariance matrices, and correlations for C and E can be calculated analogously.

Data analysis was performed in Ubuntu 22.04 using RStudio v.4.2.0 (2022-04-22, SCR_000432), and packages — tidyverse (v.1.3.1, Wickham et al., Reference Wickham, Averick, Bryan, Chang, McGowan, François, Grolemund, Hayes, Henry, Hester, Kuhn, Pedersen, Miller, Bache, Müller, Ooms, Robinson, Seidel, Spinu and Yutani2019, SCR_019186), gt (v.0.6.0, Iannone et al., Reference Iannone, Cheng and Schloerke2022) and the UMX package, (v.4.10.50 and OpenMx v2.20.6) (Bates et al., Reference Bates, Maes and Neale2019) — were used for the bivariate structural modeling of the ACE Cholesky decomposition. For the umxACE function, the arguments addCI and Intervals were set up as True; the modeling was performed using the ‘CSOLNP’ optimizer. All code is available in GitHub URL: https://github.com/NeuroGenomicsMX/TwinsMX_Astigmatism_Myopia.

Results

Considering that DZ twin pairs can be discordant for sex, we performed a chi-square test between MZ and DZ twins for the total sample by sex. The chi-square test did not show significant differences in sex ratios between DZ and MZ, χ 2 (1, N = 2798) = 1.83, p = .18. Figure 2 shows subgroups or pairs segregated by zygosity and sex (2A) and distribution by age group (2B). No differences in distribution by age group were observed between MZ and DZ pairs, χ 2 (4, N = 1399) = 7.1623, p = .13.

Figure 2. A. Twin pairs segregated by zygosity and sex. No differences by group were observed (p = .18). B. Twin pairs segregated by zygosity and age group. No differences between DZ and MZ pairs were observed (p = .13).

Note: MZ, monozygotic; DZ, dizygotic; MZF, MZ female; MZM, MZ male; DZF, DZ female; DZM, DZ male; DZO, DZ opposite sex.

The prevalence of astigmatism, myopia, and their comorbidity —that is, their co-occurrence — were characterized in the whole sample. Considering the whole sample, 50.90% (1424/2798) of the individuals had at least one of the two diagnoses (astigmatism or myopia). Specifically, 5.5% (155) of the individuals were diagnosed only with astigmatism, 14.58% (408) only with myopia, and 30.77% (861) were diagnosed with both. There were no differences between the distribution of these three groups by zygosity, MZ versus DZ, χ 2 (2, n = 1424) = 2.21, p = .33, nor by sex, χ 2 (2, n = 1424) = 0.23, p = .89; see Figures 3A and 3B respectively.

Figure 3. Prevalence of astigmatism, myopia, and their comorbidity in the sample. Three groups are shown: Astigmatism and No myopia; No astigmatism and Myopia; Astigmatism and Myopia. Segregated by zygosity (A) or by sex (B). No differences between groups were observed by zygosity: monozygotic (MZ) vs. dizygotic (DZ), χ2(2, N = 1424) = 2.21, p = .33, nor by sex, χ2(2, N = 1424) = 0.23, p = .89.

Astigmatism

Among 1399 families, the prevalence of astigmatism was 36% (1016/2798). Concordance rates results showed that MZ twins had a significantly higher astigmatism concordance than DZ, .74 versus .50; χ2(1) = 40.20, p = 2.29 × 10-10 (Table 1).

Table 1. Astigmatism concordance rates in Mexican twins

Note: MZ, monozygotic; DZ, dizygotic; MZF, monozygotic female; MZM, monozygotic male; DZF, dizygotic female; DZM, dizygotic male; DZOS, dizygotic opposite sex. Probandwise concordance between All MZ and All DZ groups was tested by Likelihood Ratio Test. χ2(1)= 40.20, p = 2.29 × 10-10. Significant concordance rate difference between groups was observed.

Myopia

The prevalence of myopia was 45% (1269/2798). The concordance rate was significantly higher for MZ than for DZ twins, .74 versus .55, χ2(1) = 33.09, p = 8.80 × 10-9 (Table 2).

Table 2. Myopia concordance rates in Mexican twins

Note: MZ, monozygotic; DZ, dizygotic; MZF, monozygotic female; MZM, monozygotic male; DZF, dizygotic female; DZM, dizygotic male; DZOS, dizygotic opposite sex. Probandwise concordance between All MZ and All DZ groups was tested by Likelihood Ratio Test. χ2(1) = 33.09, p = 8.80 × 10-9. Significant concordance rate difference between groups was observed.

Additional Analysis for Complete Pairs Only

The same statistics were estimated for the subsample that included the participant-report of both twins (243 pairs). Consistent with the previous results (considering the report from one twin about both twins), MZ twins showed higher concordance rates for astigmatism, χ2(1) = 14.72, p = 1.20 × 10-4 (Table 3) and myopia, χ2(1) = 12.08, p = 5.0 × 10-4 (Table 4).

Table 3. Astigmatism concordance rate in pairs of Mexican twins

Note: MZ, monozygotic; DZ, dizygotic. Probandwise concordance between All MZ and All DZ groups was tested by Likelihood Ratio Test. χ2(1) = 14.72, p = 1.20 × 10-4. Significant concordance rate difference between groups was observed.

Table 4. Astigmatism concordance rate in pairs of Mexican twins

Note: MZ, monozygotic; DZ, dizygotic. Probandwise concordance between All MZ and All DZ groups was tested by Likelihood Ratio Test. χ2(1) = 12.08, p = 5.0 × 10-4. Significant concordance rate difference between groups was observed.

Heritability and Cross-Trait Correlation

The Akaike information criterion (AIC) showed that the AE model had a better fitting that the ACE model (Table 5). The estimates and their corresponding 95% CI for ACE and AE are detailed in Figure 4.

Table 5. Model fitting for ACE model and comparison with more parsimonious models

Note: *2 × log likelihood. AIC, Akaike information criterion. The AE model in bold type showed the best fit according to the AIC. Each model is compared to the original ACE; the p value shows whether the fitting of the model significantly decreased after removing a parameter, such as A in CE or C in AE models. Consequently, the AE model p = .275 did not differ and to favor parsimony this was selected as the best one.

Figure 4. Bivariate path model for astigmatism and myopia. A. Estimates and 95% CI for the full ACE model (fitting: −2 × log likelihood = 5892.59). B. Adjusted estimates and 95% CI for the AE model, which was suggested by the AIC (ΔAIC = −2.12) with the best fitting (−2 × log likelihood = 5896.4) as the most parsimonious model.

Note: ACE model refers to the additive genetic (A) effects, and common (C), and unique (E) environmental influences on a trait. AIC, Aikake information criterion.

The additive genetic effects or heritability (A) for astigmatism (a2 11) was estimated at .81 (95% CI [.74, .82]) with residual or nonshared environmental contributions (e2 11) E = .19 (95% CI [.17, .25]). Meanwhile, heritability (a21 2 + a22 2) for myopia was estimated at A = .81 (95% CI [.73, .89]) and E (e21 2 + e22 2) = .19 (95% CI [.15, .21]). Additionally, bivariate modeling allowed us to estimate the cross-trait correlation; for this model the genetic correlation was rA = .80 (95% CI [0.77, 0.83]), and nonshared environmental correlation rE = .89 (95% CI [0.84, 0.91]). Finally, the phenotypic correlation between astigmatism and myopia due to additive genetic influences was rP = .79 (95% CI [.76, .82]), and the phenotypic correlation due to nonshared environmental influences was estimated at .21 (95% CI [.18, .24]). The calculations for these bivariate effects and cross-trait correlations are carefully detailed in (Munn et al., Reference Munn, Stallings, Rhee, Sobik, Corley, Rhea and Hewitt2010).

Discussion

This study aimed to estimate the concordance rates and heritability of myopia and astigmatism in Mexican twins. Given the genetically diverse ancestral composition of the Mexican population (García-Ortiz et al., Reference García-Ortiz, Barajas-Olmos, Contreras-Cubas, Cid-Soto, Córdova, Centeno-Cruz, Cicerón-Arellano, Flores-Huacuja, Baca, Bolnick, Snow, Flores-Martínez, Ortiz-Lopez, Reynolds, Blanchet, Morales-Marín, Velázquez-Cruz, Kostic and Orozco2021; Martínez-Cortés et al., Reference Martínez-Cortés, Salazar-Flores, Fernández-Rodríguez, Rubi-Castellanos, Rodríguez-Loya, Velarde-Félix, Muñoz-Valle, Parra-Rojas and Rangel-Villalobos2012), this study is relevant to better understand the relevance of genes on these diagnoses in genetically admixed populations that are typically underrepresented in research. The results showed higher concordance rates for myopia and astigmatism in monozygotic (MZ) twins compared to dizygotic (DZ) twins. The estimated heritability was .81 for each of the traits, astigmatism and myopia, and the genetic correlation (rA = .80) suggests that both traits are influenced by a shared set of genes.

Although a correlation lower than one does not necessarily imply that the set of shared genes has a similar effect on both astigmatism and myopia (Posthuma, Reference Posthuma and Kim2009), the high value of the genetic correlation in this study supports the conclusion that astigmatism and myopia share a genetic basis and overlap in their genetic effects. Accordingly, a genomewide association study (GWAS) in a sample with European ancestry found that the NPLOC4/TSPAN10 (17q25.3) gene cluster, which has previously been linked to myopia and other ocular disturbances (e.g., Plotnikov et al., Reference Plotnikov, Shah, Rodrigues, Cumberland, Rahi, Hysi, Atan, Williams and Guggenheim2019), was also associated with astigmatism (Shah, Li et al., Reference Shah, Li, Zhao, Tedja, Tideman, Khawaja, Fan, Yazar, Williams, Verhoeven, Xie, Wang, Hess, Nickels, Lackner, Pärssinen, Wedenoja, Biino, Concas, Uitterlinden and Bailey-Wilson2018). Another study in individuals from the UK and Canada showed that keratoconus, a corneal deformity and thickness associated with early stages of myopia and astigmatism, involved approximately 500 genetic loci, suggesting a highly polygenic architecture of ocular refraction errors (He et al., Reference He, Han, Ong, Hewitt, Mackey, Gharahkhani and MacGregor2022). The present study highlights the genetic overlap between astigmatism and myopia, and further research is needed to identify the specific shared or unique loci contributing to the etiology of these conditions. The higher concordance rates and heritability estimates in this study indicate that these refractive errors have a strong genetic contribution in the Mexican population.

Our results are consistent with prior research on the heritability of astigmatism and myopia in various populations. For astigmatism, studies have demonstrated higher correlations within MZ twins compared to DZ twins for factors such as refractive error, axial length, and corneal curvature (Dirani et al., Reference Dirani, Islam, Shekar and Baird2008; Lyhne et al., Reference Lyhne, Sjolie, Kyvik and Green2001; Teikari et al., Reference Teikari, O’Donnell, Kaprio and Koskenvuo1989). In the case of myopia, a Chinese study found a higher concordance rate in MZ twins (.65) than in DZ twins (0.46) (Lin & Chen, Reference Lin and Chen1987). Our findings, with concordance rates of .74 and .55 for MZ and DZ twins respectively reveal a similar trend. Currently, it is understood that myopia results from the interplay of multiple genes and genetic variants that influence eye growth and retinal signaling (Williams et al., Reference Williams, Hysi and Hammond2017).

The demographic analyses showed no differences in the distribution of age nor sex between MZ and DZ twins, suggesting that differences in demographics (p > .05) do not explain our results. Additionally, our results show a higher prevalence of myopia (45%) than astigmatism (36%) in the Mexican population, which is consistent with those previously observed by Gomez-Salazar et al. (Reference Gomez-Salazar, Campos-Romero, Gomez-Campaña, Cruz-Zamudio, Chaidez-Felix, Leon-Sicairos, Velazquez-Roman, Flores-Villaseñor, Muro-Amador, Guadron-Llanos, Martinez-Garcia, Murillo-Llanes, Sanchez-Cuen, Llausas-Vargas, Alapizco-Castro, Irineo-Cabrales, Graue-Hernandez, Ramirez-Luquin and Canizalez-Roman2017). Additionally, there was a higher number of participants that reported being diagnosed with both astigmatism and myopia, instead of only one diagnosis, and this is not different as a function of zygosity (MZ vs. DZ) or sex (MZ vs. DZ). This finding suggests a phenotypic link between these two traits.

While biometric measures are used to diagnose astigmatism, for example, measuring the meridian of anterior corneal surface (also known as K1) and the steep meridian of the anterior corneal surface (also known as K2) to estimate the spherical equivalent and the autorefraction of the eyes (Dirani et al., Reference Dirani, Islam, Shekar and Baird2008), we had no access to any of these values. Requesting such information can limit the extent of participant recruitment, particularly in populations like those in Mexico, where obtaining large sample sizes with these biometric measures is a geographic and economic challenge. In these circumstances, participant self-reported data acquired through online methods can offer a significant advantage for twin studies, particularly in terms of size and geographic representation (Grjibovski et al., Reference Grjibovski, Magnus, Midelfart and Harris2006; Hur et al., Reference Hur, Bogl, Ordoñana, Taylor, Hart, Tuvblad, Ystrom, Dalgård, Skytthe and Willemsen2019).

Our results were robust even when considering reports for the pair from only one of the twins. The primary analysis conducted on 1399 families and the analysis on 243 complete pairs both replicated the results for myopia and astigmatism. Furthermore, the consistency of participant and co-twin reports was observed to be high, with 80.45% agreement for astigmatism and 84.36% for myopia. This suggests that the participant and co-twin reports were highly reliable and supports the value of using participant-reported data in twins’ studies, especially when only one of the twins can provide information. This method allows the effective use of data obtained through electronic records, making research possible for underrepresented populations. Nevertheless, further research should compare the in-person physical examination and participant-reported data to assess the similarity and reliability of results and address this inherent limitation when using participant-reported data.

One shortcoming of the study is that the limited sample size prevented us from conducting subgroup analyses by zygosity and sex. Future research should aim to overcome this limitation by increasing the sample size, in order to investigate genetic differences as a function of sex in greater detail. Although a high reliability (above 85%) between perceived zygosity and DNA-tested zygosity has been reported (J. Chen et al., Reference Chen, Li, Chen, Yang, Zhang, Duan and Ge2010; Hardiansyah et al., Reference Hardiansyah, Hamrefors, Siqueiros, Falck-Ytter and Tammimies2021; Ooki & Asaka, Reference Ooki and Asaka2004; Reed et al., Reference Reed, Plassman, Tanner, Dick, Rinehart and Nichols2005), another inherent limitation in this study is that the DNA validation of the zygosity was not performed; further research might address the concern for this Mexican sample.

Also, given the high genetic influence demonstrated in the current results, it is also desirable to explore possible genetic factors and variations in the Mexican population through techniques such as GWASs (Nakanishi et al., Reference Nakanishi, Yamada, Gotoh, Hayashi, Yamashiro, Shimada, Ohno-Matsui, Mochizuki, Saito, Iida, Matsuo, Tajima, Yoshimura and Matsuda2009; Shah, Li et al., Reference Shah, Li, Zhao, Tedja, Tideman, Khawaja, Fan, Yazar, Williams, Verhoeven, Xie, Wang, Hess, Nickels, Lackner, Pärssinen, Wedenoja, Biino, Concas, Uitterlinden and Bailey-Wilson2018). In addition to the strong genetic contribution identified here, it is relevant to note that, according to the model fitting, the shared environmental influence was not significant enough to be included in the model, suggesting that the common lifestyle in the twins’ families has no significant influence on the variability of being diagnosed with astigmatism or myopia. However, it is also important to consider individual environmental factors such as nutrition, the use of electronic devices, and near-work to be explored in future Mexican twin samples to understand their role in the prevalence in different traits, including refractive errors.

Finally, it is not unexpected that one of the first twin studies focused on examining the concordance rates of refraction errors in human eyes. Twin studies afford a unique chance to investigate conditions such as astigmatism and myopia. In conclusion, our study affirms that the likelihood of developing astigmatism and myopia in the Mexican population is significantly shaped by genetic factors.

Data availability statement

The data and analyses supporting the findings of this study will be available after accepted publication at GitHub URL: https://github.com/NeuroGenomicsMX/TwinsMX_Astigmatism_Myopia. Personal data containing information that could compromise the privacy of the participants will not be available.

Acknowledgments

We would like to thank all the twins for their willingness to participate and for taking the time to be part of the registry. To the social media and designers’ team: Mauricio Guzman and Andrea Bermeo. And to all the team of the TwinsMX: Ian Espinosa, Regina Casa Madrid, Arantza Piña, Brenda Gónzalez, Xochil Díaz, and Itzamná Sanchez for their support in twin experimental sessions. This work received technical support from Luis Aguilar, Alejandro León, and Jair García of the Laboratorio Nacional de Visualización Científica Avanzada. We also thank Carina Uribe Díaz, Leopoldo González Santos and Alejandra Castillo Carbajal for their technical support, and Michael C. Jeziorski for editing this manuscript.

Financial support

This work was supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) (Grant CF-2019 No. 6390). In addition, MER is supported by the Al & Val Rosenstrauss Fellowship from the Rebecca L. Cooper Medical Research Foundation, Australia (F20231230).

Competing interests

None.

Ethical statement

The study protocol was reviewed and approved by the Research Ethics Committee of the Institute of Neurobiology at UNAM. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

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Figure 0

Figure 1. Bivariate path modeling for astigmatism and myopia. Cholesky decomposition in latent variables: A (genetic contribution), C (shared environment influence), and E (residual or nonshared environmental influences). A1 represents the latent variable (i.e., the set of genes) that contributes to astigmatism (path a11) and myopia (path a21). A2 is the second latent variable (i.e., a second set of genes) affecting myopia. Also shown are the respective variables for shared and nonshared environmental contributions (C and E).

Figure 1

Figure 2. A. Twin pairs segregated by zygosity and sex. No differences by group were observed (p = .18). B. Twin pairs segregated by zygosity and age group. No differences between DZ and MZ pairs were observed (p = .13).Note: MZ, monozygotic; DZ, dizygotic; MZF, MZ female; MZM, MZ male; DZF, DZ female; DZM, DZ male; DZO, DZ opposite sex.

Figure 2

Figure 3. Prevalence of astigmatism, myopia, and their comorbidity in the sample. Three groups are shown: Astigmatism and No myopia; No astigmatism and Myopia; Astigmatism and Myopia. Segregated by zygosity (A) or by sex (B). No differences between groups were observed by zygosity: monozygotic (MZ) vs. dizygotic (DZ), χ2(2, N = 1424) = 2.21, p = .33, nor by sex, χ2(2, N = 1424) = 0.23, p = .89.

Figure 3

Table 1. Astigmatism concordance rates in Mexican twins

Figure 4

Table 2. Myopia concordance rates in Mexican twins

Figure 5

Table 3. Astigmatism concordance rate in pairs of Mexican twins

Figure 6

Table 4. Astigmatism concordance rate in pairs of Mexican twins

Figure 7

Table 5. Model fitting for ACE model and comparison with more parsimonious models

Figure 8

Figure 4. Bivariate path model for astigmatism and myopia. A. Estimates and 95% CI for the full ACE model (fitting: −2 × log likelihood = 5892.59). B. Adjusted estimates and 95% CI for the AE model, which was suggested by the AIC (ΔAIC = −2.12) with the best fitting (−2 × log likelihood = 5896.4) as the most parsimonious model.Note: ACE model refers to the additive genetic (A) effects, and common (C), and unique (E) environmental influences on a trait. AIC, Aikake information criterion.