May 2023
Volume 64, Issue 5
Open Access
Genetics  |   May 2023
Familial Whole Exome Sequencing Study of 30 Families With Early-Onset High Myopia
Author Affiliations & Notes
  • Entuan Yang
    Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
  • Jifeng Yu
    Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
  • Xue Liu
    Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
  • Huihui Chu
    Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
  • Li Li
    Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, China
  • Correspondence: Li Li, Department of Ophthalmology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China; [email protected]
Investigative Ophthalmology & Visual Science May 2023, Vol.64, 10. doi:https://doi.org/10.1167/iovs.64.5.10
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      Entuan Yang, Jifeng Yu, Xue Liu, Huihui Chu, Li Li; Familial Whole Exome Sequencing Study of 30 Families With Early-Onset High Myopia. Invest. Ophthalmol. Vis. Sci. 2023;64(5):10. https://doi.org/10.1167/iovs.64.5.10.

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Abstract

Purpose: This study was conducted to investigate potential candidate pathogenic genes in early-onset high myopia (eoHM) in families with eoHM.

Methods: Whole-exome sequencing was performed on probands with eoHM to identify potential pathogenic genes. Sanger sequencing was used to verify the identified gene mutations causing eoHM in first-degree relatives of the proband. The identified mutations were screened out by bioinformatics analysis combined with segregation analysis.

Results: A total of 131 variant loci, involving 97 genes, were detected in the 30 families. A total of 28 genes (37 variants), which were carried by 24 families, were verified and analyzed by Sanger sequencing. We identified five genes and 10 loci associated with eoHM, which have not been reported in previous research. Hemizygous mutations in COL4A5, NYX, and CACNA1F were detected in this study. Inherited retinal disease-associated genes were found in 76.67% (23/30) of families. Genes that can be expressed in the retina in the Online Mendelian Inheritance in Man database were found in 33.33% (10/30) of families. Mutations in the genes associated with eoHM, including CCDC111, SLC39A5, P4HA2, CPSF1, P4HA2, and GRM6, were detected. The mutual correlation between candidate genes and phenotype of fundus photography was revealed in our study. The eoHM candidate gene mutation types contain five categories: missense mutations (78.38%), nonsense (8.11%), frameshift mutation (5.41%), classical splice site mutation (5.41%), and initiation codon mutation (2.70%).

Conclusions: Candidate genes carried by patients with eoHM are closely related to inherited retinal diseases. Genetic screening in children with eoHM facilitates the early identification and intervention of syndromic hereditary ocular disorders and certain hereditary ophthalmopathies.

In recent times, myopia has shown a trend of an increasing incidence, younger age-of-onset, and high progressive rates,1 which can develop into serious high myopia (HM). High myopia is defined as an equivalent spherical lens (SE) ≤ −6.00D.2 What deserves attention is that HM can result in complications such as cataracts, chorioretinal atrophy, macular degeneration, macular holes, and retinal detachment,3 which can lead to blindness. Despite numerous studies exploring the pathogenesis of myopia, the pathogenesis remains unclear, given its complex etiology. At present, it is clear that the pathogenesis of myopia is regulated by environmental and genetic factors. Research indicates that augmenting time dedicated to outdoor pursuits may mitigate myopia prevalence,4,5 and individuals with advanced education and extended work hours exhibit a markedly elevated incidence of myopia.69 The familial aggregation of myopia, particularly HM, underscores the significance of genetic factors in the pathogenesis of myopia. Several family-based studies have shown that the heritability of ametropia—the proportion of phenotypic variation caused by genetic factors—can be as high as 50% to 90%.10 
HM can be classified into two types based on age of onset: early-onset high myopia (eoHM) and late-onset high myopia (loHM). Compared with loHM, eoHM occurs in children before school age, is less affected by environmental factors, and entails briefer durations of close-proximity visual engagement. Refractive errors in young children are primarily influenced by genetic factors, providing a valuable opportunity to investigate the genetic underpinnings of HM. Currently, 18 pathogenic genes associated with eoHM have been detected by whole-exome sequencing (WES) with or without linkage analysis. Most of them are through autosomal dominant (AD) inheritance (SLC39A5,11 BSG,12 CCDC111,13 SCO2,14 ZNF644,15 P4HA2,16 CPSF1,17 TNFRSF21,18 NDUFAF7,19 DZIP1, XYLT120). Some of them show autosomal recessive (AR) inheritance (CTSH,21 GRM6,12 LEPREL1,21,22 LRPAP121,23, LOXL324), and X-linked (XL) inheritance (ARR3,25 OPN1LW26). We conducted WES on nonsyndromic children with eoHM, identified rare genetic variations, and performed Sanger sequencing on at least the first-degree relatives of the probands. We then combined this with pedigree and phenotypic analysis of family members to explore the genetic factors contributing to eoHM and expand the candidate genes associated with HM. 
Materials
We enlisted 30 families with children experiencing eoHM and their first-degree relatives for participation in our study. The probands were composed of children younger than or equal to seven years old (preschool children in China) who were diagnosed with HM. After atropine-induced (1% atropine) pupil dilation, their subjective refraction examination revealed SE ≤ −6.00D. Affected family members were defined as individuals with SE ≤ −6.00D. The study was conducted in compliance with the Helsinki Declaration and approved by the Ethics Committee of Beijing Children's Hospital, Capital Medical University. We obtained informed consent from all participants and guardians of children younger than eight years of age. We collected DNA from the venous blood of 30 probands and their first-degree relatives. The ocular examinations, including best corrected visual acuity, fundus photography, axial length, ocular position, slit lamp, ophthalmoscope examination, mydriatic examination, and lens insertion optometry, were performed in probands by professional ophthalmologists. We investigated the genetic information of families and collected information such as probands’ mean daily duration of close-proximity visual engagement (reading picture books and music score, using smartphones and tablet computer) and mean daily time spent outdoors. The specifics of the probands and their respective pedigrees are consolidated within the Table
Table.
 
Potential Pathogenic Mutations and Clinical Data of Probands with eoHM
Table.
 
Potential Pathogenic Mutations and Clinical Data of Probands with eoHM
Through ophthalmological examination and consultation, it was ascertained that none of the study participants had developed systemic diseases associated with myopia, including Stickler syndrome, Marfan syndrome, Ehlers-Danlos syndrome, Marshall syndrome, Bohring-Opitz syndrome, Weill-Marchesani syndrome, and Wagner syndrome, among others. 
Methods
Genomic DNA was extracted from the venous blood of each proband. The Agilent SureSelect Human All ExonV6 Kit (Agilent Technologies, Santa Clara, CA, USA) was used for exome capture. The Illumina Novaseq 6000 platform (Illumina Inc., San Diego, CA, USA) was used for genomic DNA sequencing to generate 150-bp paired-end reads with a minimum coverage ×10 for ∼99% of the genome (mean coverage of ×100). 
After sequencing, basecall file conversion and demultiplexing were performed with bcl2fastq software (Illumina), and then the results were aligned to the reference human genome (hs37d5) using the Burrows-Wheeler Aligner (bwa),27 and duplicate reads were marked using sambamba tools.28 Single nucleotide variants (SNVs) and indels were called with SAMtools to generate gVCF files.29 
The copy number variants were detected with CoNIFER software (V0.2.2).30 Annotation was performed using ANNOVAR (June 8, 2017).31 Annotations included minor allele frequencies from public control datasets, as well as deleteriousness and conservation scores, enabling further filtering and assessment of the likely pathogenicity of variants. 
Filtering of rare variants was performed as follows: (1) variants with an MAF less than 0.01 in 1000 genomic data (1000g_all),32 esp6500siv2_all (http://evs.gs.washington.edu/EVS), gnomAD data (https://doi.org/10.1101/030338), and Novo-Zhonghua exome database from Novogene were determined; (2) SNVs occurring in exons or splice sites (splicing junction 10 bp) were further analyzed; (3) synonymous SNVs that are not relevant to the amino acid alternation predicted by dbscSNV were discarded; the small fragment non-frameshift (<10 bp) indel in the repeat region defined by RepeatMasker was discarded; (4) variations were screened according to scores from SIFT,33 Polyphen,34 MutationTaster,35 and CADD software.36 The potentially deleterious variations were reserved if the score from more than half of these four software programs supported the harmfulness of variations.37 Sites (>2 bp) that did not affect alternative splicing were removed. 
Sanger sequencing on the family members of the proband was performed for the mutations with a higher likelihood of pathogenicity and in those with inadequate evidence of a pathogenic role but that were likely to be pathogenic variants. The process of variant filtering has been incorporated into Figure 1. The retinal disease-related genes involved in this study were obtained from the RetNet website (https://sph.uth.edu/retnet/), with 281 loci causing genetic retinal disease as of October 7, 2022. 
Figure 1.
 
The process of variant filtering.
Figure 1.
 
The process of variant filtering.
Results
Among the 30 probands included, there were 14 boys (46.6%) and 16 girls (53.3%) (Table). Their average age at diagnosis of HM was 3.35 ± 1.66 years, and their average examination age was 5.97 ± 2.93 years. Twenty of the probands (66.7%) enrolled in the study were younger than age seven. The average SE of the 30 included probands’ right eyes was −6.45 ± 2.51 D, and that of the left eyes was −6.96 ± 1.55 D. Among them, there were two cases of monocular HM with the other eye having myopia less than −5 D, two cases of monocular HM with the other eye having myopia less than −2 D, and one case of monocular HM with the other eye having hyperopia. The SE of the patient's hyperopic eye is 1.375 D, and the patient is four years old. Because his hyperopic eye is considered to be physiological at this age, we classified him as having eoHM. The axial length of the probands’ right eyes was 25.11 ± 1.29 mm, and that of the left eyes was 25.46 ± 1.33 mm. The fundus photography of the probands showed leopard-like fundus phenotype in 14 cases, myopic crescent phenotype in 11 cases, lacquer cracks in three cases, thinning or straightening of vessels in 14 cases, and none of the above fundus changes in 11 cases. Retinal angiography (FFA) of a proband with a heterozygous COL11A1 mutation was not ruled out from ocular Stickler syndrome; finally, the patient was treated with cryotherapy for retinal degeneration in the left eye. 
A total of 131 variation sites were detected in the 30 families, including 97 genes. In our study, we identified five genes and 10 loci associated with eoHM, which have not been reported in previous research (Table). Certain genes recur in multiple families. We quantified the number of families exhibiting such genes, and the corresponding proportion is depicted in Figure 2
Figure 2.
 
Three genes (ABCA4, COL11A1, LTBP2) were detected in four families, six genes were detected in three families (CCDC111, LRIT3, GPR179, COL2A1, SLC39A5, COL18A1), and 13 genes were detected in two families (GRM6, CACNA1F, PAH, CACNA2D4, FBN2, ADAMTSL4, NYX, ADAMTS17, SEMA4A, MYO7A, MYOC, USH2A, ZNF469).
Figure 2.
 
Three genes (ABCA4, COL11A1, LTBP2) were detected in four families, six genes were detected in three families (CCDC111, LRIT3, GPR179, COL2A1, SLC39A5, COL18A1), and 13 genes were detected in two families (GRM6, CACNA1F, PAH, CACNA2D4, FBN2, ADAMTSL4, NYX, ADAMTS17, SEMA4A, MYO7A, MYOC, USH2A, ZNF469).
The 37 loci identified across 24 families underwent Sanger sequencing validation and segregation analysis involving the parents (Table). In addressing myopia, a polygenic condition, we exercise extreme caution when using the ACMG guideline's PP1 evidence (co-segregation of variant and disease within families), requiring at least two instances of segregation. Our study's pedigrees reveal that some family members without candidate genes exhibit mild myopia, although not HM. We handle such families with prudence, refraining from applying co-segregation evidence. Notably, all family members carrying the variant do not suffer from inherited retinal diseases (IRD), only demonstrating a myopic phenotype. The results of WES in the probands were analyzed, and hemizygote variation was identified first. Hemizygous mutations were identified in one family with COL4A5, one family with NYX, and one family with CACNA1F, respectively. Heterozygous mutations were also identified in another family with CACNA1F and another family with NYX, respectively. 
We performed a mutual correlation in 24 families between candidate genes and mean daily duration of close-proximity visual engagement (Fig. 3), mean daily time spent outdoors in probands (Figs. 45). In 30 families, we performed a mutual correlation between candidate genes and phenotype of fundus photography in the probands (Figs. 69). 
Figure 3.
 
Candidate genes and mean daily duration of close-proximity visual engagement.
Figure 3.
 
Candidate genes and mean daily duration of close-proximity visual engagement.
Figure 4.
 
Candidate genes and mean daily time spent outdoors in probands on working day.
Figure 4.
 
Candidate genes and mean daily time spent outdoors in probands on working day.
Figure 5.
 
Candidate genes and mean daily time spent outdoors in probands on weekends.
Figure 5.
 
Candidate genes and mean daily time spent outdoors in probands on weekends.
Figure 6.
 
The correlation between candidate genes and the observed vessel thinning and straightening in fundus photography of 30 probands. The portion of the figure with annotated gene names represents the probands with vessel thinning and straightening.
Figure 6.
 
The correlation between candidate genes and the observed vessel thinning and straightening in fundus photography of 30 probands. The portion of the figure with annotated gene names represents the probands with vessel thinning and straightening.
Figure 7.
 
The correlation between candidate genes and the leopard-like fundus phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with leopard-like fundus phenotype.
Figure 7.
 
The correlation between candidate genes and the leopard-like fundus phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with leopard-like fundus phenotype.
Figure 8.
 
Correlation between candidate genes and the myopic crescent phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with myopic crescent phenotype.
Figure 8.
 
Correlation between candidate genes and the myopic crescent phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with myopic crescent phenotype.
Figure 9.
 
Correlation between candidate genes and the myopic lacquer cracks phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with lacquer cracks phenotype.
Figure 9.
 
Correlation between candidate genes and the myopic lacquer cracks phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with lacquer cracks phenotype.
Comparing the 28 genes in our study with the 281 genes published in RetNet (a website providing genes and mapped loci causing retinal diseases: https://sph.uth.edu/retnet/), we found genes related to IRD in 76.67% (23/30) of probands, including 91.89% (34/37) of the loci and 92.86% (26/28) of the genes. These genetic variants were associated with the risk of three main diseases: macular degeneration (15 families), congenital stationary night blindness (two families carry AR genetic mutations, and nine families carry XL mutations), and other retinal diseases (eight families). In our study, a similar computational filtering was performed for the list of all 468 genes associated with the retina from the Online Mendelian Inheritance in Man (OMIM) database with our candidate genes. Similarly, 50.00% of the families (15/30) carried candidate genes that could be expressed in the retina. 
We compared the detected variants with 467 refractive error related variants published in two GWAS studies,3841 identifying 11 genes consistent with those reported in GWAS research, namely GRM6, PAX6, VSX1, ABCA4, CNGB3, FBN2, ADAMTSL4, LTBP2, TRPM1, SLC39A5, and PRPF6. In our investigation, we identified four genes associated with myopia phenotypes as cataloged in the OMIM database. They were CCDC111 (MIM, 615421; phenotype, MYP22), SLC39A5 (MIM, 608730; phenotype, MYP24), P4HA2 (MIM, 600608; phenotype, MYP25), and CPSF1 (MIM, 606027; phenotype, MYP27). 
In our study, the type of mutation in the candidate genes associated with eoHM fell into five categories. The proportion is shown in Figure 10. Sequence traces with the mutations are shown in the Supplementary Information
Figure 10.
 
The type of mutations at the candidate genes associated with eoHM fall into five categories: missense mutation (78.38%), nonsense mutation (8.11%), frameshift mutation (5.41%), classical splice site mutation (5.41%), and initiation codon mutation (2.70%).
Figure 10.
 
The type of mutations at the candidate genes associated with eoHM fall into five categories: missense mutation (78.38%), nonsense mutation (8.11%), frameshift mutation (5.41%), classical splice site mutation (5.41%), and initiation codon mutation (2.70%).
Discussion
In our study, WES sequencing was performed on 30 probands, and Sanger sequencing was performed on their first-degree relatives at least. We identified five genes and 10 loci associated with eoHM, which have not been reported in previous research. Potential pathogenic mutations were found in 24 families (80.00%, 24/30), of which 37 variants were related to eoHM. 
We propose that eoHM can be categorized into syndromiceoHM and non-syndromic eoHM. Diagnosing many ocular syndromes in preschool-aged children can prove challenging, making it difficult to rule out the presence of non-syndromic HM in all eoHM cases within our study. Nonetheless, Sanger sequencing validation results from all proband parents revealed that the 37 identified mutations were all inherited, rather than de novo mutations. Of the 37 mutations, only one father with a GRM6 mutation did not exhibit HM. However, the proband carrying the GRM6 variant had HM, suggesting the possibility of incomplete penetrance for the GRM6 gene. The remaining 36 mutations were detected in the parents of the probands, with both parents carrying the same mutation presenting with simple myopia, devoid of any ocular syndrome manifestations. In the 24 families carrying candidate gene mutations, the father with the GRM6 mutation did not have HM. In contrast, five proband parents with mutations had moderate myopia, whereas 18 proband parents with mutations exhibited HM. All mutation-carrying members displayed simple myopia without syndromic ocular disease manifestations. According to our interviews, probands were exposed to electronic devices and engaged in close-range reading of picture books at an earlier age than their parents. Consequently, we cannot rule out the influence of certain environmental factors contributing to a more severe degree of myopia in probands compared to their mutation-carrying parents. 
Research has demonstrated that eoHM in children may serve as a significant characteristic of certain systemic diseases or inherited ocular disorders.42 The proportion of systemic diseases in children with HM is 13%∼19%,43,44 mainly Stickler syndrome and Marfan syndrome. HM is a common clinical feature of Stickler syndrome and Marshall syndrome. The COL11A1 gene is a common pathogenic gene in Stickler syndrome and Marshall syndrome,4547 and COL2A1 is also a common pathogenic gene in Stickler syndrome.48,49 In our research, both of these genes were identified in two families each; however, neither the father nor the mother, who shared the same mutation as the proband, exhibited any symptoms associated with systemic disorders. The 28 identified mutations were all genetic alterations observed in one parent of the proband. The onset age of some syndromes was older than the age of our probands at the time of examination. By examining parents with the same mutation for the corresponding syndromes, we can judge whether the mutation will lead to simple HM and explore candidate genes for HM. Some mutations of COL2A1 can lead to ocular-only Stickler syndrome,38 which is characterized by HM but no other system abnormalities except the eyes. The candidate genes detected in this study are also related to congenital contractural arachnodactyly (FBN2), Alport syndrome (COL4A5), and Weill-Marchesani syndrome (LTBP2), which share myopia as a common clinical feature. However, individuals carrying the identified variants in the pedigrees did not present with any clinical symptoms of these syndromes. 
The mutations of some eoHM candidate genes in our study are related to other eye diseases in the OMIM database. These eye diseases include retinitis pigmentosa (RP), cone-rod dystrophy, congenital static night blindness, achromatopsia, age-related macular degeneration, early-onset macular degeneration, Stargardt disease, and other IRD. The highest proportion of these was RP, cone-rod dystrophy, and congenital static night blindness, which were found in nine, five, and four families, respectively. There are also mutations related to diseases such as lens ectopia, glaucoma, and keratoconus. However, currently, none of the adults carrying these mutations in their families have exhibited any of the aforementioned syndromes. 
According to earlier research, 23.4% (76/325) and 23.8% (71/298) of individuals carried RetNet genes in cohorts of 325 and 298 eoHM probands, respectively.21,50 These data were calculated based on the number of probands. In our study, we found genes related to IRD in 91.89% (34/37) of loci or 92.86% (26/28) of genes, calculated using the number of genes or loci. When calculated using the number of probands, 23 of the 30 families in our research carried RetNet genes, accounting for 76.67%. Additionally, the RetNet database contained only 234 genes in previous studies, whereas our investigation expanded the RetNet gene set to 281, which is another crucial factor explaining the higher ratio observed in our research compared to previous studies. 
Sun et al.42 research on mutation types in eoHM patients revealed that missense mutation accounted for 72.5%, truncation mutation (frameshift mutation, stop gain mutation, splice site mutation) accounted for 27.5%, and missense mutation and truncation mutation accounted for 50.0%, respectively, in an RP cohort. However, in this study, 78.38% of the gene mutations in eoHM patients were missense mutations, and 21.62% were nonsense mutations, frameshift mutations, splice site mutations, and initiation codon mutations. This may be related to our small sample size. In our study, the AD gene was found to be the most frequent in the eoHM cohort, which corroborates the findings of Sun et al.42 
In two genome-wide association studies (GWAS), 12 common candidate genes related to myopia were found, including PRSS56, BMP3, KCNQ5, LAMA2, TOX, TJP2, RDH5, ZIC2, RASGRF1, GJD2, RBFOX1, and SHISA6.51,52 Li et al.53 performed WES in 298 patients with eoHM and 195 patients with retinal degeneration and did not identify the above 12 genes. By contrast, we identified 11 genes consistent with those reported in GWAS research, namely GRM6, PAX6, VSX1, ABCA4, CNGB3, FBN2, ADAMTSL4, LTBP2, TRPM1, SLC39A5, and PRPF6. A primary rationale, it seems, is that the genes associated with refractive errors have experienced substantial expansion in GWAS studies. 
Whether candidate genes of eoHM can be incorporated into candidate genes of HM relies on long-term follow-up studies of patients with eoHM. However, with regard to our observation of adult carriers of inherited mutations in current families, no one had related syndromic diseases and IRD other than simple HM. Our research has broadened the scope of mutations associated with eoHM, and investigated the correlation between phenotype and candidate genes. The candidate genes carried by eoHM patients are closely related to IRD. It is plausible that eoHM may be an early characteristics of IRD or systemic diseases in children. Therefore we propose genetic testing for children with eoHM, as the results can provide guidance for the early diagnosis and treatment of syndromic and nonsyndromic hereditary eye diseases. 
Acknowledgments
We extend our sincere gratitude to all the children and families who participated in this study. 
Supported by the National Natural Science Foundation of China (81970844). 
Disclosure: E. Yang, None; J. Yu, None; X. Liu, None; H. Chu, None; L. Li, None 
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Figure 1.
 
The process of variant filtering.
Figure 1.
 
The process of variant filtering.
Figure 2.
 
Three genes (ABCA4, COL11A1, LTBP2) were detected in four families, six genes were detected in three families (CCDC111, LRIT3, GPR179, COL2A1, SLC39A5, COL18A1), and 13 genes were detected in two families (GRM6, CACNA1F, PAH, CACNA2D4, FBN2, ADAMTSL4, NYX, ADAMTS17, SEMA4A, MYO7A, MYOC, USH2A, ZNF469).
Figure 2.
 
Three genes (ABCA4, COL11A1, LTBP2) were detected in four families, six genes were detected in three families (CCDC111, LRIT3, GPR179, COL2A1, SLC39A5, COL18A1), and 13 genes were detected in two families (GRM6, CACNA1F, PAH, CACNA2D4, FBN2, ADAMTSL4, NYX, ADAMTS17, SEMA4A, MYO7A, MYOC, USH2A, ZNF469).
Figure 3.
 
Candidate genes and mean daily duration of close-proximity visual engagement.
Figure 3.
 
Candidate genes and mean daily duration of close-proximity visual engagement.
Figure 4.
 
Candidate genes and mean daily time spent outdoors in probands on working day.
Figure 4.
 
Candidate genes and mean daily time spent outdoors in probands on working day.
Figure 5.
 
Candidate genes and mean daily time spent outdoors in probands on weekends.
Figure 5.
 
Candidate genes and mean daily time spent outdoors in probands on weekends.
Figure 6.
 
The correlation between candidate genes and the observed vessel thinning and straightening in fundus photography of 30 probands. The portion of the figure with annotated gene names represents the probands with vessel thinning and straightening.
Figure 6.
 
The correlation between candidate genes and the observed vessel thinning and straightening in fundus photography of 30 probands. The portion of the figure with annotated gene names represents the probands with vessel thinning and straightening.
Figure 7.
 
The correlation between candidate genes and the leopard-like fundus phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with leopard-like fundus phenotype.
Figure 7.
 
The correlation between candidate genes and the leopard-like fundus phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with leopard-like fundus phenotype.
Figure 8.
 
Correlation between candidate genes and the myopic crescent phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with myopic crescent phenotype.
Figure 8.
 
Correlation between candidate genes and the myopic crescent phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with myopic crescent phenotype.
Figure 9.
 
Correlation between candidate genes and the myopic lacquer cracks phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with lacquer cracks phenotype.
Figure 9.
 
Correlation between candidate genes and the myopic lacquer cracks phenotype in 30 probands. The portion of the figure with annotated gene names represents the probands with lacquer cracks phenotype.
Figure 10.
 
The type of mutations at the candidate genes associated with eoHM fall into five categories: missense mutation (78.38%), nonsense mutation (8.11%), frameshift mutation (5.41%), classical splice site mutation (5.41%), and initiation codon mutation (2.70%).
Figure 10.
 
The type of mutations at the candidate genes associated with eoHM fall into five categories: missense mutation (78.38%), nonsense mutation (8.11%), frameshift mutation (5.41%), classical splice site mutation (5.41%), and initiation codon mutation (2.70%).
Table.
 
Potential Pathogenic Mutations and Clinical Data of Probands with eoHM
Table.
 
Potential Pathogenic Mutations and Clinical Data of Probands with eoHM
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