Advertisement

BMC Medical Genetics

, 20:25 | Cite as

Analysis of genetic polymorphisms for age-related macular degeneration (AMD) in Chinese Tujia ethnic minority group

  • Shengchun Liu
  • Mingxing Wu
  • Bianwen Zhang
  • Xiaojing Xiong
  • Hao Wang
  • Xiyuan ZhouEmail author
Open Access
Research article
  • 114 Downloads
Part of the following topical collections:
  1. Genetic epidemiology and genetic associations

Abstract

Background

Age-related macular degeneration (AMD) can cause vision loss or blindness in elderly. The associations between single nucleotide polymorphism (SNP) and AMD in Chinese Tujia ethnic minority group are still unclear.

Methods

A total of 2122 Tujia volunteers were recruited and 197 of them were diagnosed with AMD (either dry or wet type).Then the blood specimens of these 197 AMD patients and 404 controls from the remaining 1925 normal Tujia volunteers were collected to detect the frequencies of 39 chosen SNPs. The Bonferroni method was used to correct the P values from the Fisher’s exact test.

Results

The mean age of the 197 AMD patients(113 males and 84 females) was 68.4197 years old. No significant differences in allelic and genotypic frequencies were found for all the 39 SNPs between the patients and controls. However, weak correlations between 10 SNPs (CFH rs1329428 TT genotype, CFH rs3753394 CC genotype and T allele, CFH rs1410996 AA genotype, CFH rs800292 AA genotype, CFH rs800292 A allele, VEGF rs833061 TT genotype and C allele, VEGF rs2010963 CG genotype, VEGFR2 rs1531289 TT genotype, ARMS2 rs10490924 TT genotype, KCTD10 rs238104 GC genotype, rs1531289 T allele and ARMS2 rs10490924 T allele) and AMD were shown.

Conclusions

The effects of 39 SNPs have found no associations with the morbidity of AMD in Chinese Tujia ethnic minority group.

Keywords

Age-related macular degeneration Single nucleotide polymorphism Chinese Tujia ethnic minority group 

Abbreviations

AMD

Age-related macular degeneration

CARMS

Clinical age-related maculopathy staging

HWE

Hardy-Weinberg equilibrium

SNP

Single nucleotide polymorphism

Background

Age-related macular degeneration (AMD) is the main cause of blindness and vision loss in old people in developed countries [1]. The formation of deposits, inflammation and ultimately neurodegeneration in the macula are typical features of the disease. In general, AMD can be divided into two subtypes: the non-exudative (dry or atropic) subtype and the exudative (wet or neovascular) subtype [2]. The development of the disease is a complex interplay of age, environmental, genetic, metabolic and many other factors [3].

Epidemiological and gene-mapping studies supported that the genetic factors played important roles in the pathogenesis of AMD [4, 5]. A genome-wide study reported 52 independently AMD associated variants by analyzing more than 15,000 patients and controls. The results also showed that rare variants could directly affect causal genes [6]. In addition, other researchers found that the loci 3p13 and 10q26 had a relationship with the complex basis of the AMD by analyzing 70 families and these genes were involved in immune response, inflammation and retina homeostasis [7]. Genome-wide association study had also been used to clarify the possible relationships between SNPs and outcomes of anti- vascular endothelial growth factor (VEGF) treatment for exudative AMD and the results showed that the age-related maculopathy susceptibility 2 (ARMS2/HTRA1) polymorphism rs10490924 might be a good marker to predict the effect of ranibizumab treatment [8].

The Chinese Tujia ethnic minority group mainly live on th mountains in the middle of China. Due to the relative isolation of mountain, this ethnic minority group may have its own specific genome. The genetic analysis of Y chromosome in Chinese Tujia ethnic minority group demonstrated that the 17 Y-STR loci were highly polymorphic [9]. Previous studies conducted by Chinese epidemiologists reported that gene variants in CFH, ARMS2 and HTRA1 were related to an increased risk of AMD in a northern Chinese population, which was partially consistent with the results of the western world [10, 11]. However, the epidemiology analysis of AMD in Chinese Tujia ethnic minority group and its potential pathogenic mechanism had not been reported.

In this study, we calculated the morbidity of AMD in 2122 Tujia volunteers. Then we analyzed the frequencies of 39 AMD-associated SNPs in 197 AMD patients and 404 normal controls. Our goal was to identify the possible pathogenic SNPs of AMD in Chinese Tujia ethnic minority group.

Methods

Patients and data collection

Our study recruited 2122 individuals who belonged to Chinese Tujia ethnic minority group in the Second Affiliated Hospital of Chongqing Medical University from January 2009 to December 2016 (Chongqing, China). Diagnosis and grading for AMD followed the standard of clinical age-related maculopathy staging (CARMS) system and maculopathy could be classified into five grades. Grade 1: no drusen or 10 small drusen without pigment abnormalities. Grade 2: approximately 10 small drusen or 15 intermediate drusen. Grade 3: approximately 15 intermediate drusen or any large drusen. Grade 4: geographic atrophy with involvement of the macular center. Grade 5: exudative AMD. Volunteers with Grade 2 or above AMD (either unilateral eye or bilateral eyes) were recruited as the patients group [12]. The ethics committee of the Second Affiliated Hospital of Chongqing Medical University approved the study and the medical records and blood samples were obtained from volunteers with written informed consents.

Single nucleotide polymorphism (SNP) selection

Target genes and SNPs were chosen according to previously published studies [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26]. As a result, 39 SNPs of 16 genes were selected.and included 8 SNPs (rs1061170, rs800292, rs3753394, rs1410996, rs1329428, rs6677604, rs380390, rs10737680) of complement factor H(CFH), 2 SNPs (rs4151667, rs641153) of complement factor B (CFB), 2 SNPs (rs9332739, rs547154) of complement C2(C2), 1 SNP (rs2241394) of complement C3(C3), 1 SNP (rs2511989) of serpin family G member 1(SERPING1), 1 SNP (rs10490924) of ARMS2, 7 SNPs (rs10033900, rsl3117504, rs11726949, rs6854876, rs11728699, rs7439493, rs4698775) of complement factor I(CFI), 2 SNPs (rs3732379, rs3732378) of C-X3-C motif chemokine receptor 1(CX3CR1), 4 SNPs (rs943080, rs3025039, rs833061, rs2010963) of VEGF, 4 SNPs (rs9554322, rs7337610, rs9582036, rs9943922) of vascular endothelial growth factor receptor (VEGFR), 1 SNP (rs1531289) of VEGFR2, 1 SNP (rs6987702) of tribbles pseudokinase 1(TRIB1),2 SNPs (rs1800775, rs3764261) of cholesteryl ester transfer protein(CETP), 1 SNP (rs2338104)of potassium channel tetramerization domain containing 10(KCTD10/MVK),1 SNP (rs8017304) of RAD51 paralog B (RAD51B) and 1 SNP (rs1883025) of ATP binding cassette subfamily A member 1(ABCA1).

DNA extraction and genotyping

Peripheral blood of AMD patients and the controls were subjected to genomic DNA extraction by using the QIAmp DNA Blood Mini Kit (Qiagen Inc., Valencia, CA, USA) and the DNAs were stored at − 80∘C. Genotype identifications of the 39 SNPs were conducted with the iPLEX Gold genotyping assay and Sequenom MassARRAY (Sequenom, CA, USA). Sequenom SNP Assay Design software (version 3.0) was used to design the primers of iPLEX reactions [27]. Primer sequences used were shown in Additional file 1: Table S1.

Statistical analysis

Hardy-Weinberg equilibrium (HWE) analysis was carried out in normal controls and no SNPs significantly deviated from HWE (P > 0.05). Fisher’s exact test was applied to evaluate the differences in allele and genotype frequencies of all SNPs between patients and healthy controls by using SPSS (version 19.0; SPSS Inc., Chicago, IL). The Bonferroni method was conducted to perform correction for multiple comparisons whereby the P value was multiplied with the number of comparisons (P corrected (Pc)) [27]. It was considered to be significant when Pc was less than 0.05.

Results

A total of 2122 volunteers aged from 50 to 90 years old were recruited to our study. The fundus examination was used to diagnose and divided the volunteers into five grades according to the clinical age-related maculopathy staging (CARMS) system. The representative images of grade 2 to 5 AMD were shown in Fig. 1. Among the 2122 volunteers, we found that 197 cases (113 males and 84 females) could be diagnosed as AMD and the mean age was 68.4ales)we foundAM (Table 1). Moreover, only 404 normal volunteers (245 males and 159 females, mean age was 63.5 ± 04 normal volu) accepted the SNPs examinations and we assigned them to the normal control group.
Fig. 1

the representative images of grade 2 to grade 5 AMDs from our patients

Table 1

The age and grade distribution of AMD patients

Age

Number(%)

AMD

Total

Grade 2

Grade 3

Grade 4

Grade 5

50–59

456(21.49%)

25(5.48%)

16

7

0

2

60–69

965(45.48%)

95(9.84%)

57

37

0

1

70–79

599(28.23%)

68(11.35%)

37

26

4

1

80-

102(4.81%)

9(8.82%)

5

3

1

0

Total

2122

197

115

73

5

4

Next, the blood specimens from AMD cases and controls were collected to detect the genome sequences. We chose 39 SNPs covering 16 genes to figure out if these SNPs could be pathogenic factors for AMD in Chinese Tujia ethnic minority group. As a result, we found that all 39 SNPs of controls met the Hardy-Weinberg equilibrium. No significant differences in both allelic and genotypic frequencies were found for all the 39 SNPs between the patient and control groups according to the Pc values (Additional file 2: Table S2). However, the P values showed weak correlations between 10 SNPs of 5 genes and AMD (Table 2). Compared with the AMD patients, the frequencies of the CFH rs1329428 TT genotype (P = 0.023, OR = 1.649 and 95% CI = 1.069–2.543), CFH rs3753394 CC genotype(P = 0.006, OR = 1.738 and 95% CI = 1.164–2.594) and T allele(P = 0.029, OR = 1.307 and 95% CI = 1.027–1.664), CFH rs1410996 AA genotype(P = 0.008, OR = 1.814 and 95% CI = 1.164–2.826) and CFH rs800292 AA genotype(P = 0.009, OR = 1.787 and 95% CI = 1.154–2.769) were decreased in the controls. On the contrary, the frequency of the CFH rs800292 A allele (P = 0.011, OR = 0.730 and 95% CI = 0.571–0.932) was increased in the controls. Moreover, the frequencies of the VEGF rs833061 TT genotype (P = 0.020, OR = 1.511 and 95% CI = 1.067–2.138) and C allele (P = 0.021, OR = 1.390 and 95% CI = 1.051–1.837), VEGF rs2010963 CG genotype(P = 0.032, OR = 1.462 and 95% CI = 1.033–2.071), VEGFR2 rs1531289 TT genotype (P = 0.040, OR = 2.025 and 95% CI = 1.020–4.022), ARMS2 rs10490924 TT genotype(P = 0.002, OR = 1.928 and 95% CI = 1.280–2.904) and KCTD10 rs238104 GC genotype (P = 0.019, OR = 1.505 and 95% CI = 1.068–2.120) were decreased and the frequencies of VEGFR2 rs1531289 T allele (P = 0.012, OR = 0.690 and 95% CI = 0.516–0.924)and ARMS2 rs10490924 T allele (P = 0.037, OR = 0.687 and 95% CI = 0.482–0.978) were increased in the controls comparing with the AMD patients.
Table 2

Genotype and allele frequencies of ten genes’ polymorphism in AMD and healthy controls

Genes

SNPs

 

Case

Control

HWE

P

Pc

OR

95%Cl

CFH

rs1329428

Total sample

197

404

     

CC

59

136

0.175

0.361

NS

0.842

0.583–1.217

CT

94

208

 

0.386

NS

0.860

0.612–1.209

TT

44

60

 

0.023

NS

1.649

1.069–2.543

C

212

480

     

T

182

328

 

0.065

NS

0.796

0.624–1.015

CFH

rs3753394

Total sample

197

403

     

CC

55

74

0.416

0.006

NS

1.738

1.164–2.594

CT

89

208

 

0.163

NS

0.784

0.558–1.104

TT

53

124

 

0.357

NS

0.837

0.573–1.223

C

199

356

     

T

195

456

 

0.029

NS

1.307

1.027–1.664

CFH

rs1410996

Total sample

190

386

     

GG

60

137

0.128

0.469

NS

0.873

0.603–1.262

GA

87

204

 

0.194

NS

0.795

0.562–1.125

AA

43

55

 

0.008

NS

1.814

1.164–2.826

G

207

478

     

A

173

314

 

0.056

NS

0.786

0.614–1.006

CFH

rs800292

Total sample

193

402

     

GG

54

140

0.190

0.095

NS

0.727

0.500–1.058

GA

95

205

 

0.686

NS

0.932

0.661–1.313

AA

44

57

 

0.009

NS

1.787

1.154–2.769

G

203

485

     

A

183

319

 

0.011

NS

0.730

0.571–0.932

VEGF

rs833061

Total sample

192

403

     

TT

113

196

0.881

0.020

NS

1.511

1.067–2.138

TC

67

171

 

0.079

NS

0.727

0.509–1.039

CC

12

36

 

0.261

NS

0.680

0.345–1.338

T

293

563

     

C

91

243

 

0.021

NS

1.390

1.051–1.837

VEGF

rs2010963

Total sample

189

396

     

CC

27

64

0.089

0.558

NS

0.865

0.531–1.408

CG

99

170

 

0.032

NS

1.462

1.033–2.071

GG

63

162

 

0.078

NS

0.722

0.502–1.038

C

153

298

     

G

225

494

 

0.349

NS

1.127

0.877–1.448

VEGFR2

rs1531289

Total sample

197

404

     

CC

118

275

0.181

0.048

NS

0.701

0.492–0.998

CT

62

111

 

0.310

NS

1.212

0.836–1.758

TT

17

18

 

0.040

NS

2.025

1.020–4.022

C

298

661

     

T

96

147

 

0.012

NS

0.690

0.516–0.924

ARMS2

rs10490924

Total sample

197

404

     

GG

57

137

0.625

0.213

NS

0.791

0.546–1.145

GT

86

200

 

0.169

NS

0.786

0.558–1.108

TT

54

66

 

0.002

NS

1.928

1.280–2.904

G

200

474

     

T

194

332

 

0.008

NS

0.722

0.567–0.920

KCTD10/MVK

rs2338104

Total sample

197

403

     

GG

19

44

0.673

0.633

NS

0.871

0.494–1.536

GC

110

184

 

0.019

NS

1.505

1.068–2.120

CC

68

175

 

0.037

NS

0.687

0.482–0.978

G

148

272

     

C

246

534

 

0.193

NS

1.181

0.919–1.518

CX3CR1

rs3732378

Total sample

193

402

     

AA

3

0

0.573

0.034

NS

  

AG

12

22

 

0.714

NS

1.145

0.554–2.365

GG

178

380

 

0.277

NS

0.687

0.348–1.356

A

18

22

     

G

368

782

 

0.084

NS

1.739

0.921–3.281

Discussion

In present study, we compared the frequencies of 39 SNPs of 16 genes between 193 AMD patients and 404 controls from Chinese Tujia ethnic minority group. It had reported that ARMS2 and CFH variants were associated with neovascular AMD in the Thai, Korean and Chinese Han population [28, 29, 30] and no previous studies focused on the associations between SNPs and AMD in Tujia ethnic minority group. Therefore, we designed this research to identify the potential associations. Finally, our results showed that no significant differences for these 39 SNPs were found between the two groups. However, the P value suggested that the AMD had weak correlations with CFH SNPs, VEGF family SNPs and ARMS2 SNP.

The major candidate genes for AMD pathogenesis were CFH and ARMS2 [31, 32]. Previous study reported gene variants in CFH and ARMS2 were related to increased risks of AMD in Chinese Han population [33]. However, our results showed negative correlation, which might be caused by the racial and sample size differences. Furthermore, VEGF gene played an important role in regulating angiogenesis and permeability [34]. The SNPs of VEGF were related to the formation of choroidal neovascularization in exudative AMD. Therefore, anti-VEGF agents had been widely used to treat the exudative AMD. The alleles in CFH, ARMS2, and VEGFA were associated with genetic anticipation and inadequate response to the anti-VEGF agents in AMD patients [35]. The relationship between the delayed functional and limited response to the injection of bevacizumab and the CFH gene polymorphism T1277C was also identified [36]. In our study, no associations were found between the SNPs of VEGF family genes and the morbidity of AMD. However, a stratified analysis had not been carried out and the relationships between SNPs of VEGF family genes and morbidity of exudative AMD were still unclear. In addition, the SNPs of VEGF family genes might affect the AMD by impacting the drug responses in Chinese Tujia ethnic minority group.

Our study had several limitations. We only chose SNPs that have been previously reported and no new SNPs were found. A genome-wide study should be carried out to find more pathogenic SNPs. Furthermore, the stratified analysis of different ages, genders or AMD types should also been used to deeply investigate the associations between the SNPs and the AMD morbidity in Chinese Tujia ethnic minority group. Last, we only recruited a very small sample size of patients in our study and the representativeness of our findings was limited. In the future, we would collect more patients to perform the SNP detections.

Conclusions

In sum, the chosen 39 SNPs had no associations with the morbidity of AMD in Chinese Tujia ethnic minority group.

Notes

Acknowledgements

Not applicable.

Funding

This study was supported by Epidemiological investigation of Han and Tujia AMD in Southwest China and study of related gene polymorphisms(cstc2015shmszx120058). The funding body was mainly used in the specimens collection and data analysis.

Availability of data and materials

The datasets used during the present study are available from the corresponding author upon reasonable request.

Authors’ contributions

XZ made substantial contributions to conception and designed the whole research; Acquisition of data and analysis and interpretation of data were mainly performed by SL, MW, BZ, XX and HW. All authors agreed to be accountable for all aspects of the work. The final version of the manuscript were approved all authors.

Ethics approval and consent to participate

The ethics committee of the Second Affiliated Hospital of Chongqing Medical University approved the study and the medical records and blood samples were obtained from volunteers with written informed consents.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary material

12881_2019_756_MOESM1_ESM.xlsx (12 kb)
Additional file 1: Table S1. Primer sequences we used to detect the 39 SNPs were listed in the table. (XLSX 11 kb)
12881_2019_756_MOESM2_ESM.xls (102 kb)
Additional file 2: Table S2. The distributions of allelic and genotypic frequencies for 39 SNPs were listed in the table. The details of HWE, P value, Pcorrect value, OR and 95%CI were also shown. (XLS 102 kb)

References

  1. 1.
    DeAngelis MM, Owen LA, Morrison MA, Morgan DJ, Li M, Shakoor A, Vitale A, Iyengar S, Stambolian D, Kim IK, Farrer LA. Genetics of age-related macular degeneration (AMD). Hum Mol Genet. 2017;26:R246.CrossRefGoogle Scholar
  2. 2.
    Zhang Y, Chioreso C, Schweizer ML, Abramoff MD. Effects of Aflibercept for Neovascular age-related macular degeneration: a systematic review and meta-analysis of observational comparative studies. Invest Ophthalmol Vis Sci. 2017;58:5616–27.PubMedPubMedCentralGoogle Scholar
  3. 3.
    Al-Zamil WM, Yassin SA. Recent developments in age-related macular degeneration: a review. Clin Interv Aging. 2017;12:1313–30.CrossRefGoogle Scholar
  4. 4.
    Chou R, Dana T, Bougatsos C, Grusing S, Blazina I. Screening for impaired visual acuity in older adults: updated evidence report and systematic review for the US preventive services task force. JAMA. 2016;315:915–33.CrossRefGoogle Scholar
  5. 5.
    Maller J, George S, Purcell S, Fagerness J, Altshuler D, Daly MJ, Seddon JM. Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration. Nat Genet. 2006;38:1055–9.CrossRefGoogle Scholar
  6. 6.
    Fritsche LG, Igl W, Bailey JN, Grassmann F, Sengupta S, Bragg-Gresham JL, Burdon KP, Hebbring SJ, Wen C, Gorski M, Kim IK, Cho D, Zack D, Souied E, Scholl HP, Bala E, Lee KE, Hunter DJ, Sardell RJ, Mitchell P, Merriam JE, Cipriani V, Hoffman JD, Schick T, Lechanteur YT, Guymer RH, Johnson MP, Jiang Y, Stanton CM, Buitendijk GH, Zhan X, Kwong AM, Boleda A, Brooks M, Gieser L, Ratnapriya R, Branham KE, Foerster JR, Heckenlively JR, Othman MI, Vote BJ, Liang HH, Souzeau E, McAllister IL, Isaacs T, Hall J, Lake S, Mackey DA, Constable IJ, Craig JE, Kitchner TE, Yang Z, Su Z, Luo H, Chen D, Ouyang H, Flagg K, Lin D, Mao G, Ferreyra H, Stark K, von Strachwitz CN, Wolf A, Brandl C, Rudolph G, Olden M, Morrison MA, Morgan DJ, Schu M, Ahn J, Silvestri G, Tsironi EE, Park KH, Farrer LA, Orlin A, Brucker A, Li M, Curcio CA, Mohand-Said S, Sahel JA, Audo I, Benchaboune M, Cree AJ, Rennie CA, Goverdhan SV, Grunin M, Hagbi-Levi S, Campochiaro P, Katsanis N, Holz FG, Blond F, Blanche H, Deleuze JF, Igo RP Jr, Truitt B, Peachey NS, Meuer SM, Myers CE, Moore EL, Klein R, Hauser MA, Postel EA, Courtenay MD, Schwartz SG, Kovach JL, Scott WK, Liew G, Tan AG, Gopinath B, Merriam JC, Smith RT, Khan JC, Shahid H, Moore AT, McGrath JA, Laux R, Brantley MA Jr, Agarwal A, Ersoy L, Caramoy A, Langmann T, Saksens NT, de Jong EK, Hoyng CB, Cain MS, Richardson AJ, Martin TM, Blangero J, Weeks DE, Dhillon B, van Duijn CM, Doheny KF, Romm J, Klaver CC, Hayward C, Gorin MB, Klein ML, Baird PN, den Hollander AI, Fauser S, Yates JR, Allikmets R, Wang JJ, Schaumberg DA, Klein BE, Hagstrom SA, Chowers I, Lotery AJ, Leveillard T, Zhang K, Brilliant MH, Hewitt AW, Swaroop A, Chew EY, Pericak-Vance MA, DeAngelis M, Stambolian D, Haines JL, Iyengar SK, Weber BH, Abecasis GR, Heid IM. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat Genet. 2016;48:134–43.CrossRefGoogle Scholar
  7. 7.
    Majewski J, Schultz DW, Weleber RG, Schain MB, Edwards AO, Matise TC, Acott TS, Ott J, Klein ML. Age-related macular degeneration--a genome scan in extended families. Am J Hum Genet. 2003;73:540–50.CrossRefGoogle Scholar
  8. 8.
    Yamashiro K, Mori K, Honda S, Kano M, Yanagi Y, Obana A, Sakurada Y, Sato T, Nagai Y, Hikichi T, Kataoka Y, Hara C, Koyama Y, Koizumi H, Yoshikawa M, Miyake M, Nakata I, Tsuchihashi T, Horie-Inoue K, Matsumiya W, Ogasawara M, Obata R, Yoneyama S, Matsumoto H, Ohnaka M, Kitamei H, Sayanagi K, Ooto S, Tamura H, Oishi A, Kabasawa S, Ueyama K, Miki A, Kondo N, Bessho H, Saito M, Takahashi H, Tan X, Azuma K, Kikushima W, Mukai R, Ohira A, Gomi F, Miyata K, Takahashi K, Kishi S, Iijima H, Sekiryu T, Iida T, Awata T, Inoue S, Yamada R, Matsuda F, Tsujikawa A, Negi A, Yoneya S, Iwata T, Yoshimura N. A prospective multicenter study on genome wide associations to ranibizumab treatment outcome for age-related macular degeneration. Sci Rep. 2017;7:9196.CrossRefGoogle Scholar
  9. 9.
    Yang YR, Jing YT, Zhang GD, Fang XD, Yan JW. Genetic analysis of 17 Y-chromosomal STR loci of Chinese Tujia ethnic group residing in Youyang Region of Southern China. Leg Med (Tokyo). 2014;16:173–5.CrossRefGoogle Scholar
  10. 10.
    Zhuang W, Li H, Liu Y, Zhao J, Ha S, Xiang W, Bai X, Li Z, Han Y, Sheng X. Association of specific genetic polymorphisms with age-related macular degeneration in a northern Chinese population. Ophthalmic Genet. 2014;35:156–61.CrossRefGoogle Scholar
  11. 11.
    Sundaresan P, Vashist P, Ravindran RD, Shanker A, Nitsch D, Nonyane BA, Smeeth L, Chakravarthy U, Fletcher AE. Polymorphisms in ARMS2/HTRA1 and complement genes and age-related macular degeneration in India: findings from the INDEYE study. Invest Ophthalmol Vis Sci. 2012;53:7492–7.CrossRefGoogle Scholar
  12. 12.
    Seddon JM, Sharma S, Adelman RA. Evaluation of the clinical age-related maculopathy staging system. Ophthalmology. 2006;113:260–6.CrossRefGoogle Scholar
  13. 13.
    Cascella R, Strafella C, Longo G, Manzo L, Ragazzo M, De Felici C, Gambardella S, Marsella LT, Novelli G, Borgiani P, Sangiuolo F, Cusumano A, Ricci F, Giardina E. Assessing individual risk for AMD with genetic counseling, family history, and genetic testing. Eye (Lond). 2017;32:446–50.Google Scholar
  14. 14.
    Cobos E, Recalde S, Anter J, Hernandez-Sanchez M, Barreales C, Olavarrieta L, Valverde A, Suarez-Figueroa M, Cruz F, Abraldes M, Perez-Perez J, Fernandez-Robredo P, Arias L, Garcia-Layana A. Association between CFH, CFB, ARMS2, SERPINF1, VEGFR1 and VEGF polymorphisms and anatomical and functional response to ranibizumab treatment in neovascular age-related macular degeneration. Acta Ophthalmol. 2017;96:e201–12.Google Scholar
  15. 15.
    Maguire MG, Ying GS, Jaffe GJ, Toth CA, Daniel E, Grunwald J, Martin DF, Hagstrom SA. Single-nucleotide polymorphisms associated with age-related macular degeneration and lesion phenotypes in the comparison of age-related macular degeneration treatments trials. JAMA Ophthalmol. 2016;134:674–81.CrossRefGoogle Scholar
  16. 16.
    Ansari M, McKeigue PM, Skerka C, Hayward C, Rudan I, Vitart V, Polasek O, Armbrecht AM, Yates JR, Vatavuk Z, Bencic G, Kolcic I, Oostra BA, Van Duijn CM, Campbell S, Stanton CM, Huffman J, Shu X, Khan JC, Shahid H, Harding SP, Bishop PN, Deary IJ, Moore AT, Dhillon B, Rudan P, Zipfel PF, Sim RB, Hastie ND, Campbell H, Wright AF. Genetic influences on plasma CFH and CFHR1 concentrations and their role in susceptibility to age-related macular degeneration. Hum Mol Genet. 2013;22:4857–69.CrossRefGoogle Scholar
  17. 17.
    Huang L, Li Y, Guo S, Sun Y, Zhang C, Bai Y, Li S, Yang F, Zhao M, Wang B, Yu W, Khor CC, Li X. Different hereditary contribution of the CFH gene between polypoidal choroidal vasculopathy and age-related macular degeneration in Chinese Han people. Invest Ophthalmol Vis Sci. 2014;55:2534–8.CrossRefGoogle Scholar
  18. 18.
    Dong Y, Li ZD, Fang XY, Shi XF, Chen S, Tang X. Association between SERPING1 rs2511989 polymorphism and age-related macular degeneration: meta-analysis. Int J Ophthalmol. 2015;8:385–94.PubMedPubMedCentralGoogle Scholar
  19. 19.
    Yu Y, Bhangale TR, Fagerness J, Ripke S, Thorleifsson G, Tan PL, Souied EH, Richardson AJ, Merriam JE, Buitendijk GH, Reynolds R, Raychaudhuri S, Chin KA, Sobrin L, Evangelou E, Lee PH, Lee AY, Leveziel N, Zack DJ, Campochiaro B, Campochiaro P, Smith RT, Barile GR, Guymer RH, Hogg R, Chakravarthy U, Robman LD, Gustafsson O, Sigurdsson H, Ortmann W, Behrens TW, Stefansson K, Uitterlinden AG, van Duijn CM, Vingerling JR, Klaver CC, Allikmets R, Brantley MA Jr, Baird PN, Katsanis N, Thorsteinsdottir U, Ioannidis JP, Daly MJ, Graham RR, Seddon JM. Common variants near FRK/COL10A1 and VEGFA are associated with advanced age-related macular degeneration. Hum Mol Genet. 2011;20:3699–709.CrossRefGoogle Scholar
  20. 20.
    Velazquez-Villoria A, Recalde S, Anter J, Bezunartea J, Hernandez-Sanchez M, Garcia-Garcia L, Alonso E, Ruiz-Moreno JM, Araiz-Iribarren J, Fernandez-Robredo P, Garcia-Layana A. Evaluation of 10 AMD associated polymorphisms as a cause of choroidal neovascularization in highly myopic eyes. PLoS One. 2016;11:e0162296.CrossRefGoogle Scholar
  21. 21.
    Ma B, Dang G, Yang S, Duan L, Zhang Y. CX3CR1 polymorphisms and the risk of age-related macular degeneration. Int J Clin Exp Pathol. 2015;8:9592–6.PubMedPubMedCentralGoogle Scholar
  22. 22.
    Xiang W, Zhuang W, Chi H, Sheng X, Zhang W, Xue Z, Pan B, Liu Y. Evaluating VEGFR1 genetic polymorphisms as a predisposition to AMD in a cohort from northern China. Ophthalmic Genet. 2016;37:388–93.CrossRefGoogle Scholar
  23. 23.
    Sharma NK, Gupta A, Prabhakar S, Singh R, Sharma S, Anand A. Single nucleotide polymorphism and serum levels of VEGFR2 are associated with age related macular degeneration. Curr Neurovasc Res. 2012;9:256–65.CrossRefGoogle Scholar
  24. 24.
    Restrepo NA, Spencer KL, Goodloe R, Garrett TA, Heiss G, Buzkova P, Jorgensen N, Jensen RA, Matise TC, Hindorff LA, Klein BE, Klein R, Wong TY, Cheng CY, Cornes BK, Tai ES, Ritchie MD, Haines JL, Crawford DC. Genetic determinants of age-related macular degeneration in diverse populations from the PAGE study. Invest Ophthalmol Vis Sci. 2014;55:6839–50.CrossRefGoogle Scholar
  25. 25.
    Chu XK, Meyerle CB, Liang X, Chew EY, Chan CC, Tuo J. In-depth analyses unveil the association and possible functional involvement of novel RAD51B polymorphisms in age-related macular degeneration. Age (Dordr). 2014;36:9627.CrossRefGoogle Scholar
  26. 26.
    Wang Y, Wang M, Han Y, Zhang R, Ma L. ABCA1 rs1883025 polymorphism and risk of age-related macular degeneration. Graefes Arch Clin Exp Ophthalmol. 2016;254:323–32.CrossRefGoogle Scholar
  27. 27.
    Huang Y, Yu H, Cao Q, Deng J, Huang X, Kijlstra A, Yang P. The Association of Chemokine Gene Polymorphisms with VKH and Behcet's disease in a Chinese Han population. Biomed Res Int. 2017;2017:1274960.PubMedPubMedCentralGoogle Scholar
  28. 28.
    Zhou TQ, Guan HJ, Hu JY. Genome-wide analysis of single nucleotide polymorphisms in patients with atrophic age-related macular degeneration in oldest old Han Chinese. Genet Mol Res. 2015;14:17432–8.CrossRefGoogle Scholar
  29. 29.
    Ruamviboonsuk P, Tadarati M, Singhanetr P, Wattanapokayakit S, Kunhapan P, Wanitchanon T, Wichukchinda N, Mushiroda T, Akiyama M, Momozawa Y, Kubo M, Mahasirimongkol S. Genome-wide association study of neovascular age-related macular degeneration in the Thai population. J Hum Genet. 2017;62:957–62.CrossRefGoogle Scholar
  30. 30.
    Woo SJ, Ahn J, Morrison MA, Ahn SY, Lee J, Kim KW, DeAngelis MM, Park KH. Analysis of genetic and environmental risk factors and their interactions in Korean patients with age-related macular degeneration. PLoS One. 2015;10:e0132771.CrossRefGoogle Scholar
  31. 31.
    Klein R, Myers CE, Meuer SM, Gangnon RE, Sivakumaran TA, Iyengar SK, Lee KE, Klein BE. Risk alleles in CFH and ARMS2 and the long-term natural history of age-related macular degeneration: the beaver dam eye study. JAMA Ophthalmol. 2013;131:383–92.CrossRefGoogle Scholar
  32. 32.
    Almeida LN, Melilo-Carolino R, Veloso CE, Pereira PA, Bastos-Rodrigues L, Sarubi H, Miranda DM, Soubrane G, De Marco L, Nehemy MB. Association analysis of CFH and ARMS2 gene polymorphisms in a Brazilian cohort with age-related macular degeneration. Ophthalmic Res. 2013;50:117–22.CrossRefGoogle Scholar
  33. 33.
    Yang X, Hu J, Zhang J, Guan H. Polymorphisms in CFH, HTRA1 and CX3CR1 confer risk to exudative age-related macular degeneration in Han Chinese. Br J Ophthalmol. 2010;94:1211–4.CrossRefGoogle Scholar
  34. 34.
    Batioglu F, Demirel S, Ozmert E, Abdullayev A, Bilici S. Short-term outcomes of switching anti-VEGF agents in eyes with treatment-resistant wet AMD. BMC Ophthalmol. 2015;15:40.CrossRefGoogle Scholar
  35. 35.
    Smailhodzic D, Muether PS, Chen J, Kwestro A, Zhang AY, Omar A, Van de Ven JP, Keunen JE, Kirchhof B, Hoyng CB, Klevering BJ, Koenekoop RK, Fauser S, den Hollander AI. Cumulative effect of risk alleles in CFH, ARMS2, and VEGFA on the response to ranibizumab treatment in age-related macular degeneration. Ophthalmology. 2012;119:2304–11.CrossRefGoogle Scholar
  36. 36.
    Medina FM, Alves Lopes da Motta A, Takahashi WY, Carricondo PC, dos Santos Motta MM, Melo MB, Vasconcellos JP. Pharmacogenetic effect of complement factor H gene polymorphism in response to the initial intravitreal injection of bevacizumab for wet age-related macular degeneration. Ophthalmic Res. 2015;54:169–74.CrossRefGoogle Scholar

Copyright information

© The Author(s). 2019

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  1. 1.Department of Ophthalmologythe Second Affiliated Hospital of Chongqing Medical UniversityChongqingChina
  2. 2.Chongqing Key Laboratory of Ophthalmology and Chongqing Eye InstituteChongqingChina

Personalised recommendations