Myopia is a common ocular condition which like many other diseases comes about due to the effect of more than one factor. A lot of research has gone into finding out what the main cause of myopia is. Many researchers believe that a combination of genetic and environmental factors induce myopia development. Currently no treatment exists to prevent myopia development. So in order to understand its pathophysiology, some researchers try to locate and identify the genes that are associated with myopia. This review will summarise the current genetic methodologies used to locate myopia genes and evidence that shows myopia has a genetic origin. Current myopia genes that have been identified will also be reported.
Myopia is simply defined as a condition where near objects are seen clearly but objects further away in the distance appear blurred (Dirani et al., 2006a). This in effect is due to the light rays coming from an object entering the eye and focussing in front of the retina, thus producing a blurred image. If this is left uncorrected in an individual, it can lead to social and economic repercussions to arise within a population. This is more apparent in underdeveloped countries where health care services are neither readily available nor of good quality. Nevertheless, this blurred image can be corrected via the use of spectacles (concave lenses), contact lenses or refractive surgery. Myopia can be classified by its aetiology, age of onset, clinical appearance and more frequently its degree. This is often done by dividing myopia into two parts; low and high (pathological) myopia. Low myopia is defined as less than or equal to -5.99 dioptres and high myopia as more than or equal to -6.00 dioptres. Pathological myopia is another name for high myopia because it is often associated with other ocular and systemic conditions. Another reason for this name is that very high degrees of myopia influence degenerative changes in the eye such as; retinal detachment and glaucoma. Thus increasing the chance of one’s vision becoming severely impaired (Tang et al., 2008). Myopia currently affects approximately 1.6 billion people worldwide (Dirani et al., 2006a). Its incidence and prevalence has been continually increasing globally over the past few decades and it tends to affect some countries more than others. Myopia is very common in several parts of Asia including Singapore, Hong Kong, China and Japan (Feldkämper and Schaeffel, 2003). The most likely cause of this is a change in environment, for example, industrialisation, which understandably changes people’s lifestyles. This change allows people to use their eye sight in ways they had not used before, such as near work activities for long periods of time i.e. reading and computer usage. Several studies have found that myopic prevalence rate is higher in children who do more near work activities than others (Zylberman et al., 1993; Hepsen et al., 2001; Saw et al., 2002). This leads one to believe that environmental factors are the main cause of an individual developing myopia. However, the dissimilarity in prevalence rates between different ethnicities is also a point to note. For example, in recent studies it was found that the prevalence rate of myopia in Europe and North America was higher than in Africa (Katz et al., 1997; Kempen et al., 2004; Kleinstein et al., 2003). Nevertheless it was also found that myopia affects the Asian population more when compared to other populations, as it has the highest prevalence rate (Saw et al., 1996). This proposes that genetics play a role in myopia development as well. In order to see how much of a role it plays, researchers tend to carry out familial and twin investigations. Currently, no treatment exists for the prevention of myopia development in humans. So to understand its pathophysiology, researchers try to identify as many myopia genes as possible. In doing this, they hope to understand the mechanisms involved in myopia development, which could make it possible to design therapies that can stop the onset and progression of myopia. This dissertation will explore the methods that researchers use to establish regions of chromosomes where possible myopia genes exist. Moreover, this dissertation will review the numerous studies carried out that provide evidence of genes affecting myopia onset and progression. Myopia genes that have been located and identified up until now will also be reported.
To grasp the fundamental principles of genetic analysis, an appreciation of the way genes are located on a chromosome is essential. This in turn will help to give a better understanding on the genetics of myopia. The way to identify genes for a condition like myopia includes the use of known DNA sequences i.e. genetic markers.
A genetic marker is an inherited genetic trait (either a single gene or DNA sequence) with a known location on a chromosome. This enables researchers to perform genetic mapping (process of assigning genes to particular positions on chromosomes) and further developing their understanding of genetic diseases. There are two genetic markers that are frequently used by geneticists; Single Nucleotide Polymorphisms (SNPs) and Microsatellites. Microsatellites are situated between genes whereas SNPs are within genes.
A SNP is defined as variation occurring in the DNA sequence between members of a species. This variation comes about when a single nucleotide in a particular DNA sequence of an individual, differs between the single nucleotide in the same DNA sequence shared by other members of a species (Brookes, 1999). A SNP is used to compare genes between individuals that have a common characteristic i.e. myopia.
Microsatellites are pieces of DNA sequences that consist of repeated units of base pairs. These base pairs have varied lengths in different alleles. Microsatellites enable unknown gene locations to be set with respect to the known microsatellite location. Furthermore, they indicate which alleles are more closely related to each other (Goldstein et al., 1995).
As long as a trait can be distinguished from others traits then genetic mapping is possible, regardless of whether the trait’s mechanism is known or not. This helps researchers investigating genes that cause myopia, as much of its pathophysiology still remains unclear. Genetic mapping tends to be used as a means to locate genes on a chromosome. Two examples include linkage analysis and association studies which have been explained below.
Linkage studies involve searching for genetic markers that are regularly present in people that are affected by a disease and absent in people that are not affected by a disease. Two loci (either two disease genes, a genetic marker and a disease gene or two genetic markers) are said to be linked if they are found to be in close proximity of each other on the same chromosome. The closer the two loci are on the same chromosome, the smaller the chance of recombination (new combination of alleles on chromosomes in offspring that was not present in the parents) of the alleles occurring and the greater the chance of co-segregation (tendency for loci of close proximity on the same chromosome to be inherited together) taking place in meiosis (Elston, 1998). So the aim of linkage analysis is to see if a genetic marker is linked to the disease gene. If there is evidence of such a link then one would assume that the genetic marker is close to the disease gene (Tang et al., 2008). Performing linkage analysis studies result in broad regions of chromosomes being found which have a high probability that the disease gene is present in that area. This technique of gene mapping can be broken down into model based (parametric) and model free (non parametric) methods.
Parametric methods concentrate on the co-segregation of the two loci of interest (Tang et al., 2008). The further away two loci are on one chromosome; the more likely they are to recombine and vice versa. To quantify an association between the two loci, a statistical test known as logarithm of odds (LOD) score is used (Morton, 1955). A LOD score tells us whether there is any evidence of linkage between the two loci present, and if there is then how significant the association is between them. Traditionally, a LOD score of greater than or equal to 3.0 shows linkage is present (Morton, 1955; Lander and Schork, 1994). Parametric linkage analysis can produce powerful statistical results in Mendelian diseases (a disease resulting from the expression of an allele on one specific locus), provided a correct model of inheritance is declared (Amos and Williamson, 1993). However, it can also produce results of reduced power should it be performed when the disease being investigated is non-Mendelian i.e. caused by the effect of a number of genes (locus heterogeneity). In this case non parametric linkage analysis may be the favoured method for gene mapping (Elston, 1998).
In non-parametric linkage analysis studies an inheritance model for the disease does not need to be specified; therefore no assumptions need to be made about the genetics of the disease. Disease models can be unclear in some conditions especially in complex (multifactorial) eye diseases i.e. non-Mendelian diseases where locus heterogeneity exists. Consequently in these circumstances it is easier to perform genetic mapping using non-parametric studies rather than parametric studies (Tang et al., 2008). Non-parametric studies produce moderately powerful statistical results when investigating Mendelian diseases, unlike the highly powerful results that are obtained from parametric studies. An advantage of non-parametric studies is their ability to detect large and moderate genetic effects of complex diseases. On the other hand they are not so good at detecting small genetic effects of complex diseases (Tang et al., 2008). When comparing parametric and non-parametric methods, a point to note is that parametric studies produce more powerful results, provided the correct inheritance model stated (Amos and Williamson, 1993). As good as linkage studies are at narrowing down chromosomal regions containing a disease/trait gene, they are time consuming and DNA from many families is required. Another technique for locating disease genes is to perform association studies.
This technique provides one with the opportunity of locating a disease gene by analysing specific parts of chromosomes and seeing if they are associated with the disease or not. Association studies look to compare DNA samples from individuals with a disease (cases) and without the disease (controls). If a particular allele is seen more often in cases than in controls, then this allele is said to be positively associated with the disease (Giordano, 2005). Genetic association studies can result in possible location of disease genes on specific chromosomes. Association studies can either be family-based or population-based.
This is where samples of individuals are taken from a population containing both cases and controls, thereafter testing the frequency of specific alleles for association with a particular disease. In performing this type of association study, many researchers have found that it produces powerful results when wanting to detect small genetic effects of complex diseases (Risch and Merikangas, 1996; Morton and Collins, 1998; Risch and Teng, 1998; Tang et al., 2008; Zhang et al., 2008). A drawback that population-based studies have is that spurious association between an allele and a disease may be shown in the results due to the effects of population stratification (Lander and Schork, 1994; Deng, 2001). Population stratification has been defined well by Tang et al., (2008) as “false positive association due to ethnically mismatched cases and controls”. Several researchers have tried to reduce the effect of population stratification on population-based studies by suggesting different statistical methods (Devlin and Roeder, 1999; Pritchard et al., 2000a; Pritchard et al., 2000b; Price et al., 2006). But in order to truly eradicate this problem, family-based association studies should be performed.
Family-based studies look at the number of times the transmission of alleles occurs from parents to affected offspring in nuclear families (Giordano, 2005). The parents in this case take up the role of controls, the children of cases, and then DNA samples of the two are compared to look for association between the alleles and the disease. Association is found with the disease when these alleles are found in the affected offspring more often than expected by chance alone. The typical method which is used in many family-based association studies is the Transmission Disequilibrium Test (TDT) which was initially suggested by Spielman et al., (1993). This test studies heterozygous parents and analyses the number of times an allele of a genetic marker is transmitted to the affected offspring (Spielman and Ewens, 1996). The main advantage family-based studies have over population-based studies is that they are not susceptible to population stratification (Tang et al., 2008). However, family-based studies do have their disadvantages, including the need for many families to be recruited compared to population-based studies, which makes the study more time consuming and costly. Moreover, many parents are likely to be deceased when investigating late-onset conditions and because the parents DNA samples are needed, this type of association study is not feasible. In addition, when performing the TDT method the parents must be heterozygotes; this in turn reduces the statistical power of the results as one is limited in choosing individuals for recruitment (Giordano, 2005).
Linkage and association studies both have their own advantages and disadvantages. Linkage analysis can be spread over larger genetic distances than association studies, therefore needing a smaller amount of genetic markers to detect the chromosomal region of interest (Giordano, 2005). Association studies provide more powerful statistical results, especially in detecting small genetic effects of complex diseases in comparison to linkage analysis (Tang et al., 2008). Hence a smaller sample of individuals is required for the study (Risch and Merikangas, 1996; Giordano, 2005). Rather than using only one type of genetic marker (SNPs or microsatellites) for gene mapping, researchers tend to take up a more useful strategy where they use both markers in conjunction. Firstly microsatellites are used for linkage analysis to locate a specific gene on a broad region of a chromosome. SNPs are then used via association studies for further investigation of a more specific chromosomal region, which has been narrowed down by the microsatellites in the linkage study (Tang et al., 2008).
Many researchers perform studies to find out what the major factor influencing the onset and progression of myopia is. Twin and familial studies allow them to see whether myopia is influenced by genetics and possibly any other factors i.e. environmental factors.
Studies involving twins supply us with the most convincing evidence that myopia has a genetic component (Young et al., 2007). Most twin studies calculate heritability (ability of a condition to be transmitted from parent to child) estimates of myopia within a population to quantify the influence genes have on myopia. Angi et al., (1993) found heritability values of 0.08-0.14, in a study on 19 monozygotic twin pairs and 20 dizygotic twin pairs that had a mean age of 5 years. One would gather from these low heritability values that genetics is not a major factor in myopia development. However these results differ from those of twin studies carried out by other researchers (see table 1) and a reason for this could be due to the small sample size used. A smaller sample size leads to less accurate heritability values of a population being calculated and this makes the results of this study less reliable than others.
Heritability values of myopia from twin studies Study No. of Twin Pairs Age Heritability Kimura, (1965) Monozygotic = 33, Dizygotic = 16 15-20 .80 Hu, (1981) Monozygotic = 49, Dizygotic = 37 7-19 .61 Teikari et al., (1991) Monozygotic = 54, Dizygotic = 55 30-31 .58 Lyhne et al., (2001) Monozygotic = 53, Dizygotic = 61 20-45 .89-.94 (Adapted from Dirani et al 2006a) Hammond et al., (2001) performed a study on 226 monozygotic and 280 dizygotic twin pairs, aged between 49 and 79 years. The heritability estimates of refractive errors were found to be between 84 and 86%. However, the heritability of myopia is specific to each population, as individual populations are exposed to different environmental conditions and therefore have different gene pools (all the alleles for a gene that are present in a population) (Wojciechowski et al., 2005). Consequently, there is little chance of the exact same heritability values of myopia being found if the same twin study that Hammond et al., (2001) performed was carried out on a different population. From observing the results of the above studies and seeing the high heritability values of myopia in twins, one must conclude that this is overwhelming evidence that myopia development is strongly influenced by genetics (Teikari, 1987; Lin and Chen, 1988; Dirani et al., 2006a; Dirani et al., 2006b; Dirani et al., 2008a; Dirani et al., 2008b). The twin study model like other statistical models is dependent on assumptions regarding measurements taken in a particular study, and the way in which these measurements are taken in that study. One assumption which the twin study model relies on is the Equal Environment Assumption (EEA). This means that monozygotic and dizygotic twin pairs must share similar environment conditions (Dirani et al., 2006a). For example, if monozygotic twin pairs were to encounter more similar environments than dizygotic twin pairs in a particular study, then this would result in an overestimation of the genetic impact on the trait being investigated. This would be a confounding factor in this study and would lessen the statistical power of the results. Twin studies generally provide evidence of the genetic basis of myopia; another approach that many researchers tend to take when investigating the factors that cause myopia is to carry out familial studies (Saw et al., 1996).
Familial studies are used by researchers to see whether myopia is a hereditary condition. A way to test for this is to find out if there is a relationship between myopic parents and their offspring. Parental history of myopia is a known risk factor of myopic development in an individual (Zadnik et al., 1994; Goss and Jackson, 1996; Liang et al., 2004). Children with one myopic parent are more likely to develop myopia than children who have no myopic parents. Moreover children with both myopic parents are at an even greater risk of developing myopia (Saw et al., 2001; Mak et al., 2006). In a longitudinal study carried out by Edwards, (1998) over five years measuring the refractive error of Chinese children within Hong Kong, a relationship was not found between myopic parents and the likelihood of their children having myopia. This suggests that in fact genetics may not be a cause of myopia, which is contrary to what other researchers have found from studies carried out on Caucasian children (Zadnik et al., 1994; Mutti et al., 2002). It was concluded in the study that a confounding factor (this being that in some parents the myopia genotype may not have been expressed) may have led to such results (Edwards, 1998). This along with a study carried out by Fan et al., (2005) seem to be isolated cases with regard to genes not causing myopia, as many other researchers have produced results that propose genetics is an important factor in the development of myopia (Yap et al., 1993; Zadnik et al., 1994; Zadnik, 1997; Pacella et al., 1999; Mutti et al., 2002; Ip et al., 2007).
It has been suggested by several researchers that the mode of inheritance of myopia is Mendelian (Karlsson, 1975; Bartsocas and Kastrantas, 1981; Goss et al., 1988). The exact Mendelian inheritance pattern for myopia has not yet been established as many studies have shown different patterns of inheritance, which consist of X-linked, Autosomal Dominant and Autosomal Recessive models (Karlsson, 1975, Bartsocas and Kastrantas, 1981; Schwartz et al., 1990; Edwards and Lewis, 1991; Paluru et al., 2003).
Despite this, numerous high myopia loci with a Mendelian inheritance pattern have been located and identified through parametric linkage analysis methods. These along with their chromosome and myopic loci are as follows; Xq28, MYP1 (Schwartz et al., 1990); 18p11.31, MYP2 (Young et al., 1998a); 12q21-23, MYP3 (Young et al., 1998b); 7q36, MYP4 (Naiglin et al., 2002); 17q21-22, MYP5 (Paluru et al., 2003); 4q22-27, MYP11 (Zhang et al., 2005); 2q37.1, MYP12 (Paluru et al., 2005) and Xq23-27.2 MYP13 (Zhang et al., 2006). Nevertheless, a study performed by Ashton, (1985) on nuclear families, found minimal evidence of the Mendelian model existing in myopia. This suggests that actually Mendelian inheritance patterns may only be present in some types of myopia; namely some high myopia’s i.e. not every person who has high myopia has inherited it (high myopia) due to a Mendelian inheritance pattern. Another example of such a case is a study carried out by Farbrother et al., (2004a) on 306 individuals from 51 families, who found that the previously identified myopia locus MYP3 was shown to cause high myopia. Yet other myopia loci, MYP2 and MYP5 did not show convincing evidence that they cause high myopia. Furthermore, high myopia is said to be more inclined to have a Mendelian inheritance pattern than low myopia (Guggenheim et al., 2000). This suggests that although some high myopia’s are Mendelian diseases i.e. caused by an allele in one gene (caused by one factor); low myopia is more likely to be caused by multiple factors i.e. a complex trait (Ashton, 1985; Goss et al., 1988; Klein et al., 2005).
Familial aggregation is defined as a trait (myopia) that is seen in family members more often than expected by chance alone. Several studies have shown that familial aggregation of myopia is more prominent in siblings rather than between parents and offspring (Saw et al., 1996; Lee et al., 2001; Rose et al., 2002; Goldschmidt, 2003; Fotouhi et al., 2007). This suggests that genetic and environmental factors both affect myopia development. Even though genetics is a significant factor in predisposing an individual to myopia, it is not the only factor. This is because some types of myopia (low and some high myopia’s) are complex traits i.e. more than one factor playing a role in the expression of the condition (Tang et al., 2008).
Many low myopia loci have been located and identified by parametric and non-parametric linkage analysis methods. These along with their chromosomal and myopic loci are as follows; 22q12, MYP6 (Stambolian et al., 2004); 11p13, MYP7 (Hammond et al., 2004); 3q26, MYP8 (Hammond et al., 2004); 4q12, MYP9 (Hammond et al., 2004); 8p23, MYP10 (Hammond et al., 2004); 1q36, MYP14 (Wojciechowski et al., 2006); 1q41, MYP15 (Klein et al., 2007) and 7p21, MYP16 (Klein et al., 2007). Nevertheless, these along with the high myopia loci are not the only genes that have been located and identified as myopia genes. Other myopia loci have been found to affect an individual in such a way that they become more susceptible to develop myopia.
There are other genes that are suspected of causing myopia, most notably the PAX6 gene, which is known for playing an important role in eye development. Its purpose is so significant within the eye that mutations in this gene can lead to a variety of ocular conditions developing, such as; Peter’s anomaly, iris coloboma, congenital cataracts, aniridia and optic nerve defects (Glaser et al., 1994; Hanson et al., 1994; Azuma et al., 2003; Hever et al., 2006; Simpson et al., 2007). There are studies that have found myopia to be linked with the PAX6 gene. For example, Hammond et al., (2004) who performed linkage analysis on 221 dizygotic twin pairs found four low myopia loci as mentioned above. They also found linkage with 5 SNP’s of the ‘PAX6′ gene at chromosome locus 11p13 (MYP7) but no association, after having carried out an association analysis as well. The group therefore suggested that there is a possibility that the PAX6 gene plays a key role in the onset and progression of myopia. Nevertheless, both Mutti et al., (2007) and Simpson et al., (2007) who carried out their investigations on low myopes, found no association between the PAX6 gene and low myopia. More recently however, several researchers have carried out studies which suggest that there is an association between the PAX6 gene and high myopia, including Hewitt et al., (2007), Tsai et al., (2008) and Han et al., (2009). These findings do not provide conclusive evidence that shows the PAX6 gene really has a significant effect on causing myopia in an individual. Rather one can deduce that an association may exist but needs to be investigated further by answering questions such as; mutations in the PAX6 gene affect what type (low or high) of myopia and to what extent?
Transforming growth factor (TGF)-?-induced factor (TGIF) is a gene in which mutations can cause certain developmental problems to occur within the brain, most notably the congenital disorder holoprosencephaly (Gripp et al., 2000). This gene has been mapped to chromosome 18p11.3, which based on its location alone causes it to be typically regarded as a candidate gene for the high myopia locus MYP2. Nevertheless, Lam et al., (2003) carried out a study to see if TGIF would show association with high myopia in Chinese subjects. The group concluded from their findings that the gene is a likely candidate to cause myopia. However, recent studies carried out by Scavello et al., (2004), Hasumi et al., (2006) and Wang et al., (2009) found no association between high myopia and the TGIF gene. From these latest studies, the researchers concluded that further investigations be carried out to elucidate the association between the TGIF gene in the MYP2 locus and high myopia.
A study about another candidate gene (COL1A1) for high myopia locus MYP5, at chromosome 17q22-q23.3 found it to be associated with high myopia in Japanese subjects (Inamori et al., 2007). Nevertheless, recent investigations carried out on Japanese subjects by Liang et al., (2007) and Nakanishi et al., (2009) found no significant association with high myopia. Therefore, in order to determine whether a significant association is present between the COL1A1 gene in the MYP5 locus and high myopia, further research of this gene is needed. Both the TGIF and the COL1A1 gene have been located within a high myopia locus. This leads one to assume that both genes would be found to be responsible for high myopia. Contrary to these postulations, neither gene has consistently been found to be significantly associated with high myopia. (Scavello et al., 2004; Hasumi et al., 2006; Liang et al., 2007; Nakanishi et al., 2009; Wang et al., 2009). This may raise the question as to whether another factor (either a common environmental or genetic factor shared by the subjects) that has not been taken into account before, is influencing this apparent negative association with myopia. However, in order to answer such a question, further research must be carried out to gain a better understanding of the underlying mechanisms of both candidate genes.
Several candidate genes are investigated by researchers when genes that affect eye development are located in animals such as mice and chicken. Variations in these candidate genes are then tested for association with myopia in humans, though an association is not always found. An example being hepatocyte growth factor (HGF) located at chromosome locus 7q21, which Han et al., (2006) previously found to be a potential locus associated with myopia. HGF is known to be linked with axial length of mice, making it a promising candidate for provoking myopia development (Zhou and Williams, 1999). Nevertheless, Wang et al., (2009) found no significant association between myopia and HGF in humans. Another candidate gene which affects the axial eye growth of chicken is EGR1, yet Li et al., (2008) found it was not responsible for myopia in human subjects. In addition, the animal myopia model may not be representative of human myopia, as both humans and animals are influenced by different genetic and environmental factors that cause them to become myopic. Therefore, the visual experience that a human encounters is likely to be different to that of an animal, which questions the effectiveness of candidate gene testing using animal models (Li et al., 2008). Other myopia susceptibility genes have also been found to be associated with myopia, but as with the aforementioned genes, further studies need to be carried out. The reason for this is to replicate their findings, as they are “necessary to separate true positives from false positives”, as well as in understanding the mechanism of the gene (Zayats et al., 2009). These genes including their chromosomal loci are as follows; MYOC, 1q23 (Tang et al., 2007); COL2A1, 12q13 (Mutti et al., 2007); LUM, 12q21 (Wang et al., 2006); TGFB1, 19q13 (Lin et al., 2006) and UMODL1, 21q22.3 (Nishizaki et al., 2009).
After recognising all of the above myopia loci that have been identified by researchers, one must understand that many more myopia loci exist. This provides good reason to believe that some types of myopia are a complex trait. Another point which supports this argument is the vast number of diseases myopia is associated with. Jacobi et al., (2005) has stated that “there are some 150 genetic syndromes, defined by specific ocular and systemic disorders that are associated with various levels of myopia”. Such a large number of associated conditions provide convincing evidence of myopia being a complex trait (Feldkämper and Schaeffel, 2003); some examples are shown in table 2.
Conditions associated with myopia Ocular Conditions Systemic Conditions Albinism Downs syndrome Retinopathy of prematurity Ehlers-Danlos syndrome Familial exudative vitreoretinopathy Homocystinuria Atrophia gyrate Marfan syndrome Choroideremia Fabry disease Coloboma Postaxial polydactyly with progressive myopia Achromatopsia Stickler syndrome Microcornea Turner syndrome Myelinated nerve fibers Noonan syndrome Retinitis Pigmentosa De Lange syndrome (Adapted from Jacobi et al., 2005) Consequently, many researchers believe that environmental factors combined with genetic factors cause an individual to become myopic (Yap et al., 1993; Zadnik et al., 1994; Zadnik and Mutti, 1995; The Framingham Offspring Eye Study Group, 1996; Pacella et al., 1999). Essentially these are small effects from many genes that interact with environmental factors (Farbrother et al., 2004b; Klein et al., 2005).
A strong genetic influence for myopia is present in a population when there is high heritability, which in turn affects the incidence rate of myopia. However myopia incidence can increase in a population even when such high heritability is present. This happens when the surrounding environment changes; as is the case in many countries around the world with the increase in several near work activities such as computer use, reading and watching television (Saw et al., 2005). This suggests that near work is an important environmental factor which causes myopia, as many researchers have provided evidence of there being an association with near work (Hammond et al., 2001; Lyhne et al., 2001; Saw et al., 2001; Mutti et al., 2002; Wolffsohn et al., 2003). Furthermore, Morgan and Rose, (2005) stated that there is “little evidence to support the idea that individuals or populations differ in their susceptibility to environmental risk factors”. Nevertheless, one must acknowledge the fact that even when faced with unfavourable environmental conditions, where the incidence of myopia in a population is very high; there are individuals that do not become myopic. This gives rise to the theory that gene-environment interactions are the true cause of myopia development in individuals.
Due to the fact that both genetic and environmental factors affect the onset and progression of myopia, gene-environment interactions describe the effects caused by the complex interplay between these factors. The theory of gene-environment interactions stipulates that some individuals carry certain genetic factors, which predispose them to be either at a higher or even lower risk of developing myopia in a particular environment (Lyhne et al., 2001). A study by Chen et al., (1985), involving 238 monozygotic and 119 dizygotic twin pairs was carried out in Taiwan to test the gene-environment interaction theory. Myopic refractive error was confirmed by performing cycloplegic refraction on all participants. The twins were then asked the number of hours of reading they did per day, to see whether they were concordant or discordant. Twin pairs were said to be concordant if both twins in a pair had a difference of less than one hour spent reading in a day. Discordant twin pairs were those that had a difference of more than one hour spent reading in a day. The group then compared the reading habits between monozygotic and dizygotic twin pairs. They found that concordance rates with regards to myopia were considerably higher in concordant monozygotic (92.4%) than concordant dizygotic (62.0%) twin pairs. Similarly the concordance rates for discordant monozygotic (79.1%) twin pairs were also higher than in discordant dizygotic (37.8%) twin pairs. These results suggest that an individual develops myopia due to the complex interaction between genetic and environmental factors. However, the hereditary factor in this study was zygosity (participants were either monozygous or dizygous twins) and not parental myopia which according to Mutti et al., (2002), “sheds no light on the hypothesis of inherited susceptibility to near-work”. In other words, the results from this study do not prove the theory of gene-environment interaction but it does give an insight into the significance of heredity and near-work (Mutti et al., 2002). Other studies have also tried to prove the gene-environment interaction theory, but at present no significant results have been found (Zadnik et al., 1994; Saw et al., 2001; Mutti et al., 2002). The reason behind this seems to be due to the relatively unknown mechanism that genetic and environmental factors interact through and induce myopic development (Saw, 2003). Another relationship that affects the onset and progression of myopia is gene-gene interaction. This is described as an allele at a particular locus, affecting the expression of another allele at a different locus (Tang et al., 2008). This along with the gene-environment interaction theory is an active area of research; where approaches are being made to unravel the nature of these interactions (Liu et al., 2004; Ritchie, 2005; Wallace, 2006). Therefore, further investigation of the mechanisms behind both of these types of interactions is vital, in order to allow a broader understanding of why myopia occurs in certain individuals (Saw et al., 2000).
Current genetic mapping techniques like linkage analysis and association studies are used by researchers to identify and locate genes that cause myopia development. But both these methods have their own advantages, such as linkage analysis studies being better at detecting disease genes over a wide range of genetic distances. Association studies on the other hand, are found to be more effective in finding genes that cause complex diseases. Recently, researchers have found it more rewarding to use both techniques one after the other i.e. narrowing down chromosomal regions using linkage analysis methods, then using association studies to eventually locate the specific genes causing myopia development. These mapping techniques enable researchers to identify myopia genes without knowing the pathophysiological pathways that induce myopia onset and progression. This is useful as many loci for both low and high myopia have been located using linkage analysis methods. Although the exact genes that cause myopia have not been identified, numerous susceptibility genes have been suggested to be responsible (Zayats et al., 2009). However, these findings are not conclusive so further investigations of the associations these candidate genes have with myopia are needed. Results from such studies could give rise to a better understanding of the molecular basis of myopia and also on the mechanisms involved with myopia development. Furthermore, there is much evidence from twin and familial studies that suggest only genes influence myopia development in humans, which holds true for some high myopia’s i.e. they have a Mendelian inheritance pattern (Young et al., 2007). However, through intensive research carried out over the past few decades, researchers have come to believe that the influence of more than one factor induces myopia development, which is true for low and some types of high myopia i.e. complex trait myopia. Nevertheless, it is still not known what the relative involvement of genetic and environmental factors is with regards to the onset and progression of myopia. Moreover, the gene-environment interaction theory leads one to believe that both factors (genetic and environmental) interact with each other to influence myopia development. But the underlying mechanisms involved with these interactions are also unknown. However, the complex nature of myopia makes it difficult for researchers to assess several genetic and environmental factors along with their interactions in one study. Therefore, care should be taken when interpreting such studies with multiple and inconsistent results. This is where replication studies become useful, as they are required to confirm any associations with myopia prior to any further research being carried out. All the same, discovering these mechanisms will be vital in understanding the balance between the risk factors i.e. to what extent myopia is due to an individual’s lifestyle or defective genotype. Nonetheless, a recent break through in human genome screening made by Complete Genomics (a bio-tech research company based in America) will possibly help in answering this question. A successful attempt has been made in the past at mapping the whole human genome by the Human Genome Project. This involved the effort of hundreds of scientists from around the world for 13 years, with the final cost running over 2 billion dollars (Lauerman, 2009). Complete Genomics however, have found a way to map the whole human genome at a much faster rate than before and also at a cheaper cost. They have announced that due to recent advancements in DNA engineering technology and nanotechnology, their machines can take just one week to sequence a whole genome for only 5 thousand dollars (Lauerman, 2009). This improvement in efficiency can allow more genomes to be sequenced and compared, thus enabling us to learn more about the genetic basis of many conditions, including myopia. As our knowledge of myopia and genetics advances, it will be fascinating to see the future impact of genetics on eye care. For example, pre-symptomatic screening could be introduced to improve public health education, through giving myopia prevention advice to those individuals most likely to develop myopia. Finally, it is important to develop new therapies which aim to prevent the onset and progression of myopia in humans as this will ultimately be beneficial for the economy and society.
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