Association of FGF10 polymorphism of rs339501 with myopia: A systematic review and meta-analysis

doi:10.21203/rs.3.rs-1724595/v1

Purpose: To carry out a meta-analysis of potential genetic association studies in order to determine whether the FGF10 polymorphism rs339501 is related to myopia.

Method: All the eligible case control studies examing the association of FGF10 polymorphisms and myopia published up to 20 January 2022 were retrieved from MEDLINE, Embase, the Cochrane library, Web of Science, the China National Knowledge Infrastructure (CNKI) and the VIP database of Chinese periodicals without language restriction. Depending on the heterogeneity among studies, a fixed-effect model or a random-effect model was chosen to compute the 95% confidence intervals (95%CIs) and odds ratios (ORs) for single nucleotide polymorphism (SNP). Publication bias were analyzed by examining the symmetry of the funnel plots and further confirmed by Begg’s and Egger’s tests. Stability of the analyses was checked by the sensitivity analysis.

Results：6 studies were finally included in our analysis. The subgroup analyses focusing on Chinese population found some significant results, which mainly fell on the recessive model and homozygote model(p<0.05), especially for the high myopia, of whom the pooled results in allelic model and dominant model(p＜0.05) were also significant. Additionally, the allelic model(p＜0.05) for the correlation between SNP rs339501 and myopia was also significant in Chinese population. Unfortunately, our analysis for the overall population did not reach a statistically significant result.

Conclusion: G allele of SNP rs339501 would increase the risk of myopia for Chinese population. Large-scale researches are still needed to corroborate the associations.

FGF10

rs339501

single nucleotide polymorphism

myopia

As one of the most widespread eye conditions, myopia is a serious health problem in the world, causing heavy economic burden to the society [1]. As reported in “The Myopia Boom” published in Nature [2], prevalence of myopia in East Asia are rising at an unprecedented speed. Nowadays, up to 90% of teenagers and young adults are nearsighted. However, the etiology and mechanism of myopia have not been fully clarified [3].

Factors that are related to the occurrence and development of myopia mainly include environmental and genetic factors. The main contributing factor to myopia, in the majority of cases, is a lifestyle that involves long education time and close work. However, hereditary factors also play a crucial role in determining the degree of vulnerability to certain risk factors associated with a particular lifestyle [4]. Candidate gene-based association studies, Genome-wide association studies (GWAS), and whole-exome sequencing [5-7] have so far uncovered a variety of genetic loci related with myopia, including PAX6, ZFHX1B, VIPR2, SNTB1, and TGIF [8]. The gene of FGF10, which is a member of FGF7 subfamily of FGF family, is located on chromosome 5p12 [9]. It has been reported in all vertebrates studied, including humans and mice [10,11]. It is a 215-amino-acid paracrine signaling growth factor with a classic secretory signaling sequence. It's crucial for adult growth and tissue homeostasis [12]. Mutations in the FGF10 gene have been linked to a variety of diseases, including salivary, lacrimal gland hypoplasia, and myopia [13,14].

The first investigation into the relationship between FGF10 rs339501 and high myopia was carried out by Hsi et al[15] in 2003, and they discovered that the increased FGF10 expression caused by the G allele increased the risk for extreme myopia(spherical equivalent≤-10.0D, or axial length≥30.0mm). Additionally, they detected an increased expression of FGF10 mRNA in scleral of the form-deprivation myopia (FDM) mice. Thereafter, several studies were also conducted to verify this association. Some of them confirmed that FGF10 rs339501 would increase the risk of high myopia or extreme myopia [14, 16-17] while Yoshida et al [18] reached the conclusion that the A allele of rs339501 is linked to a higher risk of developing extreme myopia in a Japanese population, what’s more, Jiang L et al [19] couldn’t find a significant association. Therefore, we performed a meta-analysis to investigate the relationship between myopia and the rs339501 polymorphism of FGF10 gene.

Throughout the design, execution, analysis, and reporting phases, our study adhered to the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) recommendations [20].

Searching strategy

Studies included in the VIP database of Chinese periodicals, Web of Science, Embase, MEDLINE, the CNKI, the Cochrane library, and that were published from the date of inception to 20 January 2022 were searched without language limitation to identify potentially relevant studies. Search terms were based on the combination of subject headings and keywords, including myopia OR “refractive error” OR nearsighted OR “near sight”; SNP OR genotype OR polymorphism(s) OR allele OR variant(s) OR mutation(s) OR “single nucleotide polymorphism”; FGF10 OR “fibroblast growth factor 10” OR rs339501.

Study selection

Two qualified investigators (H.P.X., C.P.F.) independently evaluated the retrieved articles' eligibility. Disagreements were settled through discussion or consultation with a third investigator (Y.G.Y). All eligible studies were checked by reading the abstract first, followed by the full-text. Additional articles were found by searching the references of the retrieved articles.

Studies were considered if they matched the following criteria: (1) cohort or case control studies; (2) evaluated the association between FGF10 rs339501 and myopia or high myopia; (3) used definite diagnostic criteria for myopia (spherical equivalent(SEQ)≤-0.5D) and high myopia (SEQ≤-6.0D or axial length(AL)≥26.0mm); (4) provided sufficient data that we need to calculate an OR and its 95% CI. Abstracts, duplicate citations, reviews, full texts without available data nonhuman studies, or editorials were excluded. To obtain any missing information, corresponding authors were emailed at least twice. When the research was discovered to have been published more than once in the open public, only the most recent one was chosen for the obtaining the data.

Data extraction and quality evaluation

A data extraction form included the first authors’ surname, year of publication, mean age, ethnicity, sample size, sexes and sex ratios, definition of myopia, source of control, genotyping method, quality scores and evidence of Hardy-Weinberg equilibrium (HWE) in the control group (Table 1). The Newcastle-Ottawa Quality Assessment Scale was used to conduct the quality assessment [21].

Statistical analysis

The pooled ORs with their respective 95%CI were calculated for the allelic model (allelic G vs. A), dominant model ((GG+GA) vs. AA), recessive model (GG vs. (AG+AA）), homozygous model (GG vs. AA) and heterozygous model (AG vs. AA) respectively to measure the association of FGF10 rs339501 with myopia. Leave-one-out method was used for sensitivity analysis. To analyze the heterogeneity among the research, chi-square analysis was utilized(α=0.1), and quantitative determination of heterogeneity was performed by I² (I²<50% indicated acceptable heterogeneity, I²>50% indicated substantial heterogeneity.) The Z test was peformed to determine the significance of the pooled ORs. Visual inspection of funnel plots was used to assess publication bias first [22]. Egger's and Begg's tests were used to further assess the funnel plot's symmetry [23, 24]. RevMan 5.3 and Stata 12 were used to performed the analyses. P<0.05 was considered statistically significant.

Literature search and study characteristics

The initial search yielded 20 articles, which were then reduced to 10 after duplicates were removed. 1 article was eliminated due to unrelated topics, and 2 review articles were removed due to their publication type after screening of the abstracts. The full text of the remaining 7 studies were reviewed, during which, 1 article was excluded after full-text reading for replicate data. Finally, our meta-analysis included 6 studies(Figure 1) [14-19]. Among these studies, five studies were conducted in China [14-17, 19], one of them in Japan [18], and one of them were confined to Children [14]. The meta-analysis included 4339 cases and 4652 controls in total. The HWE test results were reported in all the included studies, and their genetic distributions were within HWE. Baseline data of these articles was listed in Tables 1.

Results of Meta-analysis

First, the heterogeneity of FGF10 rs339501 in pooled populations from China and Japan was assessed. The random-effect model was chosen for analysis since the results exhibited moderate to high heterogeneity which was unable to be easily explained in all the genetic models (Tables 2, 3, and 4). The results revealed insignificant relationship between FGF10 rs339501 and myopia in the 5 genetic models. (Table 2, Supplementary Fig 1). Further subgroup analysis was conducted basing on the ethnicity, thus data in five studies focusing on Chinese population were pooled. In the Chinese population (Table2, Fig 2), allelic model (OR = 1.11, 95%CI 1.02–1.22, p = 0.02; P_Q = 0.15; I² = 41%; fixed-effect model), recessive model (OR = 1.54, 95%CI 1.11–2.15, p = 0.01; P_Q = 0.23; I² = 29%; fixed-effect model) and homozygote model (OR = 1.57, 95% CI 1.13–2.19, p = 0.008; P_Q = 0.19; I² = 35%; fixed-effect model) represented a significant correlation between FGF10 rs339501 and myopia, while other models did not show a significant association. For high myopia populations, five genetic models all reached insignificant results (Table 3, Supplementary Fig 2). While in the subgroup analysis for Chinese population (Table3, Fig 3), the allelic (OR = 1.19, 95%CI 1.00–1.41, p = 0.04; P_Q = 0.03; I² = 62%; random-effect model), dominant (OR = 1.13, 95%CI 1.01–1.27, p = 0.03; P_Q = 0.11; I² = 46%; fixed-effect model), recessive (OR = 1.64, 95%CI 1.15–2.32, p = 0.006; P_Q = 0.11; I² = 48%; fixed-effect model), homozygote (OR = 1.79, 95%CI 1.05–3.04, p = 0.03; P_Q = 0.07; I² = 53%; random-effect model) models all showed a significant association between high myopia and FGF10 rs339501 except for the heterozygote model (OR = 1.10, 95%CI 0.97–1.23, p =0.13; P_Q = 0.34; I² = 11%; fixed-effect model). For extreme myopia populations, none of these models reached a statistically significant association. (Table 4, Supplementary Fig 3). Further subgroup analysis showed that, for the Chinese population (Table 4, Fig 4), FGF10 rs339501 was in association with extreme myopia in recessive (OR = 2.27, 95%CI 1.39–3.71, p = 0.001; P_Q = 0.15; I² = 48%; fixed-effect model) and homozygote (OR = 2.38, 95%CI 1.12–5.04, p = 0.02; P_Q = 0.11; I² = 54%; random-effect model) model.

Sensitivity analysis

We found that Yoshida’s study [18] is the main source of heterogeneity in our analyses. Even so, the results showed that removing any one of the studies did not significantly alter the pooled ORs of the remaining studies (Supplementary Fig 4, 5, 6). As a result, the results indicated that our Meta-analysis's pooled results were trustworthy and stable.

Publication Bias

Since the funnel plots were roughly symmetrical, it is possible to neglect the publishing bias. In addition, neither Begg's (Table 2, 3, 4, Supplementary Fig 7, 8, 9) nor Egger's (Table 2, 3, 4, Supplementary Fig 10, 11, 12) test indicated a significant publication bias. Therefore, there is no sufficient evidence to prove publication bias in our meta-analysis.

Myopia is thought to be a complicated multigenic disease. Genetic research on myopia remains to be a huge challenge. Therefore, the research on how genetic polymorphisms affect myopia is useful for elucidating the connection between myopia and genetics. As mentioned above, some studies had explored the effect of FGF10 polymorphism on myopia but they did not reach a consensus. The inconsistent conclusions may due to the difference in study designs, ethnicity, source of control, age range, sex ratios and so on. It may be difficult for an individual study with a small sample size to determine whether a genetic variant causes high myopia, but meta-analysis, which pools all eligible data, can produce more comprehensive outcome.

Our Meta-analysis was based on the pooled ORs from 6 eligible case-control studies consisting of 4339 cases and 4652 controls. The findings indicated a significant correlation in the Chinese population between FGF10 rs339501 and myopia, high myopia, or extreme myopia though they did not show a correlation between this allele and myopia in the overall population. These significant results mainly fell on the recessive and homozygote models, and especially for the high myopia, of whom the pooled results in allelic and dominant models were also significant. Additionally, the allelic model for the association between SNP rs339501 and myopia was also significant. Therefore, according to these findings, the G allele of SNP rs339501 might enhance the risk of myopia in the Chinese population. Chinese and Japanese people are of Asian descent, and both live in east Asia areas that have similar natural growth environment, thus their genetic research outcomes should be similar in theory. While studies in The Japanese population have found that the A allele of SNP rs339501 would increase the risk of myopia which was in contrary to studies based on the Chinese population. In order to reach more representative and comprehensive conclusions, The subgroup analysis' outcomes should be interpreted with caution. Additionally, more large and well-designed trials using standardized unbiased methods and including other ethnic groups are expected to further clarify this association.

Heterogeneity may limit the interpretation of pooled estimates. We found that Yoshida’s study [18] is the main source of the heterogeneity. Even though, none of the individual studies had a significant effect on the pooled data while being excluded, which suggested the stability of our Meta-analysis. In subgroup analysis, only Yoshida’s study [18] focused on Japanese population while others included Chinese population, thus the subgroup analysis happened to reduce the heterogeneity in the Chinese subgroup and found that Chinese populations with the rs339501 variants to G allele may have somewhat higher risks of developing myopia. The results indicated that rs339501 variants may have more effects on the development of myopia for Chinese in comparison to Japanese. However, considering there’s only one study included Japanese, and the cases were limited to the patients with extreme myopia, the pooled results in total may not be universal. Subgroup analysis also revealed some statistically significant results and some OR values which were below 2.00 would make us wonder if these associations were meaningful. Given that myopia is a mild disease that doesn’t cause much harm to our body as cancer. Also, it is universal in population, and affected jointly by gene and environment. The relatively lower ORs in these models seem to be reasonable.

FGF10 is abundant in the retina and sclera of mice [15, 25]. In the lens-induced myopia model of tree shrew, the expression of FGF10 was increased in retina after 6 hours of lens-wearing [26]. And in FDM mice, FGF10 mRNA levels were increased in the sclera of the occluded eyes [15]. Scleral remodeling is an important mechanism in the incidence and progression of myopia [27], numerous genes are related to scleral remodeling, including glycosaminoglycans (GAGs) [28], Matrix metalloproteinases (MMPs) [29], Tissue inhibitors of metalloproteinases (TIMPs) [29] and transforming growth factor-β (TGF-β) [30]. According to previous studies, MMP and TIMPs involved in scleral remodeling were mainly MMP2 and TIMP2 [31, 32] and FGF10 played a key role in controlling the extension process of lacrimal bud through regulation of GAGs, MMPs and TIMPs [33,34]. In addition, it is reported that all the FGF members would inhibit the TGF-β signaling, when they are bound to the FGF receptors [35]. As a result, it is hypothesized that FGF10 might play a role in myopia scleral remodeling by controlling the production of MMP2, TIMP2, or GAGs. SNP rs339501 is located in CHR5:44365531 (GRCh38), coding transcript intron variant of FGF10, and it is a transcription factor binding site as well as a sequence variant located within a regulatory region which may regulates the activity of transcription factors [36]. Based on the ChIP-seq data, some transcription factors (e.g., CEBPB, HIF-1A and FOS) can bind at the region where rs339501 is located [37]. However, the experimental studies exploring the effect of these transcription factors on FGF10 has not been conducted. Also, some genome-scale pathogenicity scores (e.g. DANN, CADD and FATHMM-MKL) indicated that this variant is likely pathogenic [37].

Advantages and Limitations

This is, to the best of our knowledge, the first meta-analysis to examine the relationship between FGF10 rs339501 and myopia. During the searching process, we did not use the language limitation which minimized the bias within our research. Also, among the included studies, we found no evidence of publication bias during the analysis. Additionally, the heterogeneity among the studies in each subgroup was successfully minimized by the subgroup analysis carried out in our study (most were reduced from over 50% to under 50% as mentioned above).

However, there were several limitations in our study which shouldn’t be neglected. First, the study population were only from China and Japan which meant that our results might not be applied for other ethnic groups. More studies focusing on other population should be conducted. Second, since we only used pooled estimates of a single variable, our results were not very exact. If we had had access to individual data, we could have adjusted our results for factors like age, gender, and other covariates. Third, our analysis did not take into account the potential for gene-gene or or other interactions between polymorphisms, necessitating additional research into the haplotypic effects of genes and multiple polymorphisms in more genes.

Our meta-analysis examined the relationship between myopia and the FGF10 rs339501 polymorphism, however the findings did not find a strong relation. According to the results of the subgroup analysis, the G allele of SNP rs339501 would increase the risk of myopia in the Chinese population. These significant results mainly fell on the recessive and homozygote models, and especially for the high myopia, of whom the pooled results in allelic and dominant models were also significant. And the allelic model for myopia was also significant. Therefore, more extensive researches are still required to corroborate the relationships in order to investigate this association further. Future research must take gene-gene and gene-environment interactions into account. What’s more, functional studies related to this allele, such as animal studies, should be carried out.

FGF10: Fibroblast growth factor 10; CNKI: China National Knowledge Infrastructure; OR: Odds ratio; CIs: confidence intervals; SNP: Single nucleotide polymorphism; GWAS: Genome-wide association studies; FDM: Form-deprivation myopia; MOOSE: Meta-Analysis of Observational Studies in Epidemiology; HWE: Hardy-Weinberg equilibrium; GAG: glycosaminoglycan; MMP: Matrix metalloproteinase; TIMP: Tissue inhibitors of metalloproteinase; TGF-β: transforming growth factor-β; GRCh38: CHR5:44365531; NOS: Newcastle-Ottawa Scale

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Competing interests

The authors declare that they have no competing interests.

Funding

The authors declare that they receive no funding from any corporation, companies or institutions etc.

Authors' contributions

Drs Hou and Yang contributed equally to this work. Drs Hou and Liu had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Hou, Yang.

Acquisition, analysis, or interpretation of data: Hou, Chen, Wang.

Drafting of the manuscript: Hou.

Critical revision of the manuscript for important intellectual content: Yang, Liu.

Statistical analysis: Hou, Yang.

Administrative, technical, or material support: Chen, Wang, Liu.

Study supervision: Yang, Liu.

Acknowledgements

Not applicable.

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Table 1 Characteristics of the included studies

Study (year)	Ethnicity	Sample size (case/control)	Sex ratio (male/female)	High myopia	Mean age (cases; control)	Genotyping method	Control	NOS score	HWE
Jiang, 2021	Chinese	1475 (675/800)	1.17 (795/680)	SE≤-6.0D, AL≥26.0mm SE≤-10.0D, AL≥30.0mm	41.60±20.57; 45.92±19.13 42.13±20.64; 45.92±19.13	TaqMan	Normal	8	Yes
Sun, 2019	Chinese	1800 (900/900)	1.07 (931/869)	SE≤-0.5D SE≤-6.0D	11±2.7; 11±2.4 11±2.2; 11±2.4	TaqMan	LogMAR visual acuity ≤0.1, no glasses or ophthalmic history	8	Yes
Jiang, 2019	Chinese	1768 (869/899)	1.20 (965/803)	SE≤-6.0D, AL≥26.0mm SE≤-10.0D, AL≥30.0mm	41.60±20.57; 45.92±19.13 42.13±20.64; 45.92±19.13	SNaPshot	SE -1.0-+1.0D, and had no evidence of disease in both eyes	8	Yes
Hsi, 2013	Chinese	1980 (1020/960)	3.47 (1537/443)	SE≤-6.0D	21.4±3.7; 20.6±3.3	TaqMan	SE≥-1.5D in the more myopia eye, no previous refractive surgery	8	Yes
Yang, 2013	Chinese	993 (442/551)	0.64 (386/607)	SE≤-6.0D	57.8±8.1; 57.8±8.1	SNaPshot	Healthy	7	Yes
Yoshida, 2013	Japanese	975 (433/542)	0.85 (448/527)	SE≤-10.00D	38.1±12.0; 40.6±12.0	TaqMan	-1.50D-+1.50D in both eyes	7	Yes

NOS: Newcastle-Ottawa Scale; HWE: Hardy-Weinberg equilibrium.

Table 2 Meta-analysis of FGF10 rs339501 polymorphism and susceptibility to myopia

Genetic model	population	Test of association			Test of heterogeneity		model	Begg’s test		Egger’s test
Genetic model	population	Pooled OR(95%CI)	Z value	P value	I ²	P value	model	Z value	Pr>\|z\|	t value	P>\|t\|
Allelic model (G vs A)	China	1.11(1.02-1.22)	2.28	0.02	41%	0.15	F	0.00	1.000	-1.14	0.319
	Japan	0.61(0.46-0.80)	3.52	0.0004	-	-	F
	Overall	1.03(0.85-1.24)	0.27	0.78	79%	0.0003	R
Dominant model (GG+AG vs AA)	China	1.09(0.99-1.21)	1.73	0.08	6%	0.37	F	0.00	1.000	-1.08	0.341
	Japan	0.58(0.43-0.79)	3.47	0.0005	-	-	F
	Overall	1.01(0.83-1.22)	0.08	0.94	74%	0.002	R
Recessive model (GG vs AG+AA)	China	1.54(1.11-2.15)	2.57	0.01	29%	0.23	F	0.75	0.452	-1.07	0.346
	Japan	0.48(0.17-1.34)	1.40	0.16	-	-	F
	Overall	1.32(0.84-2.10)	1.20	0.23	50%	0.07	R
Homozygote model (GG vs AA)	China	1.57(1.13-2.19)	2.67	0.008	35%	0.19	F	0.75	0.452	-1.13	0.320
	Japan	0.42(0.15-1.20)	1.61	0.11	-	-	F
	Overall	1.32(0.80-2.17)	1.10	0.27	57%	0.04	R
Heterozygote model (AG vs AA)	China	1.06(0.96-1.18)	1.16	0.25	0%	0.71	F	0.38	0.707	-1.25	0.279
	Japan	0.60(0.44-0.82)	3.22	0.001	-	-	F
	Overall	0.99(0.83-1.17)	0.14	0.89	64%	0.02	R

R: random-effect model; F: fixed-effect model.

Table 3 Meta-analysis of FGF10 rs339501 polymorphism and susceptibility to high myopia

Genetic model	population	Test of association			Test of heterogeneity		model	Begg’s test		Egger’s test
Genetic model	population	Pooled OR (95%CI)	Z value	P value	I ²	P value	model	Z value	Pr>\|z\|	t value	P>\|t\|
Allelic model (G vs A)	China	1.09(1.00-1.41)	2.10	0.04	62%	0.03	R	0.75	0.452	0.24	0.824
	Japan	0.61(0.46-0.80)	3.52	0.0004	-	-	R
	Overall	1.08(0.86-1.37)	0.67	0.50	83%	<0.0001	R
Dominant model (GG+AG vs AA)	China	1.13(1.01-1.27)	2.15	0.03	46%	0.11	F	0.75	0.452	0.30	0.782
	Japan	0.58(0.43-0.79)	3.47	0.0005	-	-	F
	Overall	1.06(0.84-1.34)	0.47	0.64	79%	0.0003	R
Recessive model (GG vs AG+AA)	China	1.64(1.15-2.32)	2.75	0.006	48%	0.11	F	0.00	1.000	0.01	0.992
	Japan	0.48(0.17-1.34)	1.40	0.16	-	-	F
	Overall	1.45(0.84-2.51)	1.34	0.18	60%	0.03	R
Homozygote model (GG vs AA)	China	1.79(1.05-3.04)	2.13	0.03	53%	0.07	R	0.00	1.000	0.01	0.993
	Japan	0.42(0.15-1.20)	1.61	0.11	-	-	R
	Overall	1.47(0.81-2.67)	1.28	0.20	66%	0.01	R
Heterozygote model (AG vs AA)	China	1.10(0.97-1.23)	1.52	0.13	11%	0.34	F	0.38	0.707	0.25	0.812
	Japan	0.60(0.44-0.82)	3.22	0.001	-	-	F
	Overall	1.02(0.83-1.26)	0.23	0.82	71%	0.004	R

R: random-effect model; F: fixed-effect model.

Table 4 Meta-analysis of FGF10 rs339501 polymorphism and susceptibility to extreme myopia

Genetic model	population	Test of association			Test of heterogeneity		model	Begg’s test		Egger’s test
Genetic model	population	Pooled OR (95%CI)	Z value	P value	I ²	P value	model	Z value	Pr>\|z\|	t value	P>\|t\|
Allelic model (G vs A)	China	1.31(0.94-1.84)	1.57	0.12	76%	0.02	R	-0.34	1.000	0.40	0.730
	Japan	0.61(0.46-0.80)	3.52	0.0004	-	-	R
	Overall	1.08(0.70-1.68)	0.36	0.72	90%	<0.00001	R
Dominant model (GG+AG vs AA)	China	1.25(0.92-1.71)	1.41	0.16	63%	0.07	R	0.34	0.734	0.55	0.635
	Japan	0.58(0.43-0.79)	3.47	0.0005	-	-	R
	Overall	1.04(0.67-1.60)	0.17	0.86	86%	<0.0001	R
Recessive model (GG vs AG+AA)	China	2.27(1.39-3.71)	3.26	0.001	48%	0.15	F	1.02	0.308	-1.65	-0.240
	Japan	0.48(0.17-1.34)	1.40	0.16	-	-	F
	Overall	1.56(0.64-3.82)	0.98	0.33	74%	0.009	R
Homozygote model (GG vs AA)	China	2.38(1.12-5.05)	2.26	0.02	54%	0.11	R	1.02	0.308	-1.64	0.244
	Japan	0.42(0.15-1.20)	1.61	0.11	-	-	R
	Overall	1.56(0.59-4.14)	0.89	0.37	78%	0.003	R
Heterozygote model (AG vs AA)	China	1.13(0.93-1.37)	1.22	0.22	28%	0.25	F	0.34	0.734	0.57	0.624
	Japan	0.60(0.44-0.82)	3.22	0.001	-	-	F
	Overall	0.98(0.68-1.42)	0.10	0.92	79%	0.002	R

R: random-effect model; F: fixed-effect model.

No competing interests reported.

Association of FGF10 polymorphism of rs339501 with myopia: A systematic review and meta-analysis

Status:

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Abstract

Figures

Background

Methods

Results

Discussion

Conclusion

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1