Mediators of Inflammation

Mediators of Inflammation / 2021 / Article
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Biomarkers for Inflammatory Eye Diseases

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Research Article | Open Access

Volume 2021 |Article ID 6622934 | https://doi.org/10.1155/2021/6622934

Alvita Vilkeviciute, Dzastina Cebatoriene, Loresa Kriauciuniene, Reda Zemaitiene, Rasa Liutkeviciene, "IL-9 and IL-10 Single-Nucleotide Variants and Serum Levels in Age-Related Macular Degeneration in the Caucasian Population", Mediators of Inflammation, vol. 2021, Article ID 6622934, 13 pages, 2021. https://doi.org/10.1155/2021/6622934

IL-9 and IL-10 Single-Nucleotide Variants and Serum Levels in Age-Related Macular Degeneration in the Caucasian Population

Academic Editor: Ayumi Ouchi
Received25 Nov 2020
Revised01 Mar 2021
Accepted05 Apr 2021
Published13 Apr 2021

Abstract

Considering the immunological impairment in age-related macular degeneration (AMD), we aimed to determine the associations of IL-9 rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884 and IL-10 rs1800871, rs1800872, and rs1800896 polymorphisms and their haplotypes, as well as the serum levels of IL-9 and IL-10 with AMD. 1209 participants were enrolled in our study. SNPs were genotyped using TaqMan SNP genotyping assays by real-time PCR method. IL-9 and IL-10 serum levels were evaluated using ELISA kits. Our study results have shown that haplotypes A-G-C-G-G and G-A-T-A-T of IL-9 SNPs are associated with the decreased odds of early AMD occurrence ( and , respectively). A set of rare haplotypes was associated with the decreased odds of exudative AMD occurrence (). Also, IL-10 serum levels were lower in exudative AMD than in controls (), patients with early AMD (), and atrophic AMD (). Furthermore, exudative AMD patients with IL-10 rs1800896 CT and TT genotypes had lower IL-10 serum concentrations than those with wild-type (CC) genotype (). In conclusion, our study suggests that IL-10 serum levels can be associated with a minor allele at IL-10 rs1800896 and exudative AMD. The haplotypes of IL-9 SNPs were also associated with the decreased odds of early and exudative AMD.

1. Introduction

Inflammation is a typical process involved in the pathogenesis of many diseases. While the inflammation is characterized as a signal transfer cascade which helps to identify and eliminate foreign materials and induce tissue recovery [1], the long-term inflammation and excessive proinflammatory molecule excretion can cause chronic conditions, such as cancer [2], type 2 diabetes mellitus [3], and neurodegenerative disorders [4], including age-related macular degeneration (AMD) [5]. AMD is a worldwide leading cause of progressive and irreversible blindness affecting 1 out of 4 people older than 75 years in developed countries [6]. Still, early signs of the disease can appear when people are in their 50s [7]. The particular pathophysiology of AMD is not clear, so this ocular impairment is described as a multifactorial disease because of its associations with environmental [8, 9] and genetic factors [10], metabolite profile [11], and even microbiome [12] changes. Increasing age, female gender, and ethnicity with the highest prevalence in Europeans at 12.3–30% have also been pinpointed as relevant risk factors [13, 14].

According to the Age-Related Eye Disease Study (AREDS), AMD is divided into early, intermediate, and late stages [15]. Early AMD is usually asymptomatic with defined lipid, protein, and collagen detachments between retinal pigment epithelium (RPE) and Bruch’s membrane (BrM) in the retina [16] called drusen and retinal pigment abnormalities. The intermediate stage is described as a presence of at least one large drusen, numerous medium-sized drusen, or geographic atrophy (GA) without extension to the center of the macula. The late AMD is divided into dry or atrophic AMD with the GA of the RPE, and neovascular or exudative AMD is diagnosed when choroidal neovascularization with detachments in the RPE, hemorrhages, and/or scars appears and causes central vision impairments [17].

Drusogenesis or accumulation of lipids and other metabolites remains a significant AMD process, resulting in chronic inflammation that directly affects RPE, choroidal capillaries, and BrM [18]. The oxidative stress caused by reactive oxygen species (ROS), nitric oxide (NO), oxidized lipoproteins, advanced glycosylation end products (AGER), and apoptotic cells is the leading cause of ocular inflammation [1921]. These accumulated substances also promote the RPE to release large amounts of different inflammatory factors. These factors’ long-term exposure leads to the degeneration and atrophy of photoreceptors and RPE cells in the retina [22]. During the inflammation, complement system components are activated whose persistent accumulation impairs RPE and promotes inflammatory cells’ (leukocytes, microglial cells, and macrophages) activation [18]; when macrophage recruitment is impaired at the site of inflammation, accumulating metabolites stimulate the release of proangiogenic mediators, such as vascular endothelial growth factor (VEGF), which induce progressive angiogenesis [19, 2325]. New, however weak, permeable, and leaking blood vessels in the choroid cause local edema leading to acute vision loss with hemorrhages and fibrotic scars [26]. These pathological processes are responsible for the degradation of BrM and the extracellular matrix and lead to exudative AMD development [24]. Lin et al. found inflammation factors (IL-10, IL-1ra, IL-9, and IL-13) that may be associated with AMD’s pathogenesis and revealed their function and regulation via specific NF-jB and JAK-STAT pathways, encouraging for the new exudative AMD treatment [23].

Genetic variations in cytokine coding genes can also cause cytokine expression changes that affect the balance between pro- and anti-inflammatory cytokines and disturb the appropriate immune response, leading to disease development. IL-10 level changes were linked to the genetic alterations mostly known as three IL-10 -1082 (rs1800896), -819 (rs1800871), and -592 (rs1800872) promoter site single-nucleotide polymorphisms (SNPs) [27]. Otherwise, only one study reported SNP in the IL-9 gene associated with the IL-9 expression. It showed that individuals carrying the A allele of the -351 polymorphism in IL-9 promoter were linked to the increased synthesis of IL-9 [28].

Considering the immunological impairment in AMD development, we aimed to determine the possible associations of IL-9 rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884 and IL-10 rs1800871, rs1800872, and rs1800896 polymorphisms and their haplotypes, as well as the serum levels of IL-9 and IL-10 with the early, exudative, and atrophic AMD. We also aimed to evaluate the associations between these polymorphisms and IL-9 and IL-10 concentrations.

2. Materials and Methods

2.1. Study Subjects

The study was approved by the Ethics Committee for Biomedical Research, Lithuanian University of Health Sciences (No. BE-2-/48).

The study groups were made of subjects who were admitted to the Hospital of Lithuanian University of Health Sciences Ophthalmology Department for preventive ophthalmological evaluation. In our study, 1209 participants were enrolled: 343 subjects in early AMD, 422 in exudative AMD, and 61 in the atrophic AMD groups. Also, 383 persons were involved as healthy controls (Table 1). Using the global AMD prevalence (8.7%) [13] and the minor allele frequencies from https://www.ncbi.nlm.nih.gov/snp/, we calculated that our collected sample sizes for the early and exudative AMD and control groups were sufficient to reach 80% or higher power for the selected SNP analysis. Unfortunately, the atrophic AMD group is too small to reach at least 80% power, and according to the power calculator (http://csg.sph.umich.edu/abecasis/cats/gas_power_calculator/), the sample size should be about 100 cases, but the atrophic AMD is a rarer condition than the early and exudative AMD in Lithuanian population to collect enough samples.


Early AMD group ()Exudative AMD group ()Atrophic AMD group ()Control group () value

Males, (%)105 (30.6)149 (35.3)22 (36.1)149 (38.9)0.019
0.291
0.672
Females, (%)238 (69.4)273 (64.7)39 (63.9)234 (61.1)
Age, median (IQR)73 (13)77 (10)80 (9)72 (11)0.266
<0.001
<0.001

Early AMD vs. control group. Exudative AMD vs. control group. Atrophic AMD vs. control group. IQR: interquartile range; : significance level, statistically significant differences observed when .

Study subjects underwent ophthalmological evaluation and general examination [29]. Participants were enrolled in our study, according to the previously published criteria [29].

2.2. Ophthalmological Evaluation

All the study subjects were evaluated by slit-lamp biomicroscopy to assess corneal and lenticular transparency. Classification and grading of lens opacities were performed according to the Lens Opacities Classification System III. On each examination, intraocular pressure was measured. Pupils were dilated with tropicamide 1%. Fundoscopy, using a direct monocular ophthalmoscope, and slit-lamp biomicroscopy with a double aspheric lens +78 diopters were performed. Results of eye examinations were recorded on most standardized forms. For a detailed analysis of the macula, stereoscopic color fundus photographs of the macula, centered at 45° and 30° to the fovea, were obtained with a Visucam NM Digital camera (Carl Zeiss Meditec AG, Germany).

All the AMD patients underwent optical coherence tomography (OCT), and fluorescence angiography was performed in patients suspected of having late AMD after the OCT examination.

The classification system of AMD formulated by the Age-Related Eye Disease Study was used: early mild AMD consisted of a combination of multiple small drusen and several intermediate (63–124 μm in diameter) drusen, or retinal pigment epithelial abnormalities and the presence of extensive intermediate drusen characterized early intermediate AMD and at least one large (≥125 μm in diameter) drusen, or geographic atrophy not involving the center of the fovea. Advanced AMD was characterized by geographic atrophy involving the fovea and/or any of the neovascular AMD features [15].

2.3. Control Group Formation

The control group consisted of subjects who had no ophthalmologic pathology on examination and agreed to participate in this study. After senile cataract surgeries, the patients were also included in the control group, while they have no other ocular comorbidity. The exclusion criteria were (i) unrelated eye disorders, e.g., high refractive error, cloudy cornea, lens opacity (nuclear, cortical, or posterior subcapsular cataract) except minor opacities, keratitis, acute or chronic uveitis, glaucoma, or diseases of the optic nerve; (ii) systemic illnesses, e.g., diabetes mellitus, malignant tumors, systemic connective tissue disorders, chronic infectious diseases, or conditions following organ or tissue transplantation; and (iii) ungraded color fundus photographs resulting from obscuration of the ocular optic system or because of fundus photograph quality.

2.4. General Medical Examination

Data on hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease, and stroke were obtained during an examination by a family doctor and gathered from medical records for all study subjects.

2.5. Polymorphism Selection

As the IL-9 and IL-10 have been shown having interactions (https://version-11-0b.string-db.org/cgi/network?networkId=bMDXv9BDi65x), five SNPs (rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884) in the IL-9 gene and three SNPs (rs1800871, rs1800872, and rs1800896) in the IL-10 gene whose minor allele frequencies in the Europe population are more than 0.1 were selected from the dbSNP database https://www.ncbi.nlm.nih.gov/snp/. The rs2069885 is a missense variant (resulting in a threonine to methionine amino acid substitution), the rs1859430 and rs2069884 intronic variants are located in the coding region of IL-9, and rs11741137 is a downstream, and rs2069870 is an upstream gene variant with no known function. Moreover, rs1859430, rs11741137, rs2069884, and rs2069885 have already been published and identified as potential biomarkers for the other diseases [3035]; also, rs2069870 along with the SNP in IL-26 demonstrated influenced susceptibility to develop allergic rhinitis [36].

The rs1800871, rs1800872, and rs1800896 SNPs are located in the upstream IL-10 promoter region and associated with transcription of IL-10 mRNA and IL-10 protein expression in vitro [37].

All these SNPs were selected for the association study in the AMD group for the first time, suggesting their role in IL-9 and IL-10 signaling pathway and AMD development.

2.6. The DNA Extraction and Genotyping

After collecting the venous blood samples, the DNA salting-out method was used for preparing genomic DNA from the white blood cells. Eight SNPs were genotyped on the Step One Plus real-time PCR system (Applied Biosystems, Foster City, USA). The TaqMan SNP genotyping assays for all eight chosen SNPs were performed according to the manufacturer’s protocol.

For quality control, 5% of randomly chosen samples for each of the 8 SNPs were selected for repetitive analysis.

2.7. Quantification of IL-10 and IL-9 Serum Levels

IL-9 and IL-10 serum levels were measured in 19 control subjects, 20 patients with early AMD, 20 atrophic AMD, and 26 exudative AMD. These two assays were performed using the Invitrogen ELISA Kit (Cat. No. BMS2081) for human IL-9, standard curve sensibility range: 3.1–200 pg/mL, sensitivity 0.5 pg/mL; Invitrogen ELISA Kit (Cat. No. KHC0101) for human IL-10, standard curve sensibility range: 0–500 pg/mL, sensitivity <1 pg/mL, following the manufacturer’s instructions, and they were analyzed on the Multiskan FC Microplate Photometer (Thermo Scientific, Waltham, MA) at 450 nm. The samples were excluded if the levels of serum cytokines were below the detection range.

2.8. Statistical Analysis

Statistical analysis was performed using the SPSS/W 20.0 software (Statistical Package for the Social Sciences for Windows, Inc., Chicago, Illinois, USA). Age and interleukin serum level data distributions were evaluated for normality by the Kolmogorov-Smirnov test. Continuous variables presented median with interquartile range (IQR) based on data distribution. For nonnormally distributed data, Mann-Whitney test was used to compare two groups, and the Kruskal-Wallis test for the three groups (statistically significant differences observed when ).

Categorical data (gender, genotype, and allele distributions) are presented as absolute numbers with percentages in brackets and compared between the early, exudative, and atrophic AMD and control groups using the test.

The impact of gene polymorphisms on early, exudative, and atrophic AMD was evaluated using binomial logistic regression analysis and presented as odds ratios (ORs) with 95% confidence interval (CI) after gender adjustment in early AMD and age in the exudative and atrophic AMD groups. Logistic regression analysis results were expressed as genetic models (codominant: heterozygotes versus wild-type homozygotes and minor allele homozygotes versus wild-type homozygotes; dominant: minor allele homozygotes and heterozygotes versus wild-type homozygotes; recessive: minor allele homozygotes versus wild-type homozygotes and heterozygotes; overdominant: heterozygotes versus wild-type homozygotes and minor allele homozygotes; the additive model was used to evaluate the impact of each minor allele on AMD). The best genetic model selection was based on the Akaike information criterion (AIC); therefore, the best genetic models were those with the lowest AIC values. We introduced an adjusted significance threshold for multiple comparisons (0.05/8, since we analyzed eight different SNPs) due to multiple association calculations [38].

Haplotype analysis was performed between the early AMD and control groups, exudative AMD and control groups, and atrophic AMD and control groups using online SNPStats software (https://www.snpstats.net/snpstats/) [39]. Two haplotype blocks were constructed based on different chromosomes where the SNPs were located. Linkage disequilibrium (LD) analysis was assessed by and measures. The associations between the haplotypes with frequencies of at least 1% and different AMD forms were calculated by logistic regression and presented as ORs and 95% CI and values adjusted for gender in early AMD and age in exudative and atrophic AMD analysis. Statistically significant differences observed when .

3. Results

3.1. Hardy-Weinberg Equilibrium

We evaluated the distributions of rs1859430, rs2069870, rs11741137, rs2069885, rs2069884, rs1800871, rs1800872, and rs1800896 genotypes in the control group using the Hardy-Weinberg equilibrium (HWE). Seven SNPs were in HWE (), but rs2069870 did not fulfill the HWE requirements because there were observed only two genotypes (Supplementary Materials, Table S1).

3.2. IL-9 (rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884) and IL-10 (rs1800871, rs1800872, and rs1800896) Analysis in Early, Exudative, and Atrophic AMD

We analyzed 8 SNPS (rs1859430, rs2069870, rs11741137, rs2069885, rs2069884, rs1800871, rs1800872, and rs1800896) and their genotype and allele distributions between the early, exudative, and atrophic AMD and control groups. Our statistical analysis revealed that genotype distributions of IL-9 rs1859430 (GG, GA, and AA) differ between the early AMD and control groups (65.6%, 27.7%, and 6.7% vs. 60.8%, 35.5%, and 3.7%, ). Any differences between study groups and IL-9 (rs2069870, rs11741137, rs2069885, and rs2069884) and IL-10 (rs1800871, rs1800872, and rs1800896) were found (Table 2).


SNPGenotypes/allelesGroup value value value
Early AMD (), (%)Exudative AMD (), (%)Atrophic AMD (), (%)Control (), (%)

IL-9 rs1859430GG225 (65.6)262 (62.1)33 (54.1)233 (60.8)0.0240.8710.426
GA95 (27.7)143 (33.9)24 (39.3)136 (35.5)
AA23 (6.7)17 (4.0)4 (6.6)14 (3.7)
G545 (79.4)667 (79.0)90 (73.8)602 (78.6)0.6250.4720.088
A141 (20.6)177 (21.0)32 (26.2)146 (21.4)

IL-9 rs2069870AA222 (64.7)262 (62.1)33 (54.1)235 (61.4)0.3490.8320.282
AG121 (35.3)160 (37.9)28 (45.9)148 (38.6)
GG0 (0)0 (0)0 (0)0 (0)
A565 (82.4)684 (81.0)94 (77.0)618 (80.7)0.4100.8530.350
G121 (17.6)160 (19.0)28 (23.0)148 (19.3)

IL-9 rs11741137CC238 (69.4)290 (68.7)41 (67.2)247 (64.5)0.1170.3890.846
CT91 (26.5)120 (28.6)18 (29.5)126 (32.9)
TT14 (4.1)12 (2.8)2 (3.3)10 (2.6)
C657 (82.7)700 (82.9)100 (82.0)620 (80.9)0.0530.2970.788
T119 (17.3)144 (17.1)22 (18.0)146 (19.1)

IL-9 rs2069885GG240 (70.0)293 (69.4)41 (67.2)250 (65.3)0.1720.4530.892
GA90 (26.2)119 (28.2)18 (29.5)123 (32.1)
AA13 (3.8)10 (2.4)2 (3.3)10 (2.6)
G570 (83.1)705 (83.5)100 (82.0)623 (81.3)0.3820.2460.867
A116 (16.9)139 (16.5)22 (18.0)143 (18.7)

IL-9 rs2069884GG239 (69.7)292 (69.2)41 (67.2)250 (65.3)0.1990.4950.892
GT91 (26.5)120 (28.4)18 (29.5)123 (32.1)
TT13 (3.8)10 (2.4)2 (3.3)10 (2.6)
G569 (82.9)704 (83.4)100 (82.0)623 (81.3)0.4240.2730.867
T117 (17.1)140 (16.6)22 (18.0)143 (18.7)

IL-10 rs1800871GG208 (60.6)252 (59.7)38 (62.3)232 (60.6)0.7050.9030.957
GA123 (35.9)152 (36.0)20 (32.8)133 (34.7)
AA12 (3.5)18 (4.3)3 (4.9)18 (4.7)
G539 (78.6)656 (77.7)96 (78.7)597 (77.9)0.7700.9180.852
A147 (21.4)188 (22.3)26 (21.3)169 (22.1)

IL-10 rs1800872GG208 (60.6)252 (59.7)38 (62.3)232 (60.6)0.7050.9030.957
GT123 (35.9)152 (36.0)20 (32.8)133 (34.7)
TT12 (3.5)18 (4.3)3 (4.9)18 (4.7)
G539 (78.6)656 (77.7)96 (78.7)597 (77.9)0.7700.9180.852
T147 (21.4)188 (22.3)26 (21.3)169 (22.1)

IL-10 rs1800896TT103 (30.0)112 (26.5)14 (23.0)103 (26.9)0.6420.3190.084
TC175 (51.0)207 (49.1)27 (44.3)203 (53.0)
CC65 (19.0)103 (24.4)20 (32.8)77 (20.1)
T381 (55.5)431 (51.1)55 (45.1)409 (53.4)
C305 (44.5)413 (48.9)67 (54.9)357 (46.6)0.4130.3500.088

Early AMD vs. control group. Exudative AMD vs. control group. Atrophic AMD vs. control group. : significance level and Bonferroni corrected significance level when .

We performed the binary logistic regression analysis to evaluate these SNPs’ impacts on early, exudative, and atrophic AMD. The analysis showed that IL-9 rs1859430 GA genotype was associated with 30% decreased odds of early AMD (; CI: 0.507-0.966; ) under the codominant model, and about 33% decreased under the overdominant model after adjustment for gender (; CI: 0.490-0.925; ). IL-9 rs11741137 CT genotype was associated with 28% decreased odds of early AMD under the overdominant model after adjustment for gender (; CI: 0.522-0.994; ). Also, we found that IL-10 rs1800896 CC genotype was associated with 2-fold increased odds of atrophic AMD (; CI: 1.078-3.759; ) under the recessive model after adjustment for age (Table 3). Since we analyzed 8 SNPs in our study, we applied the Bonferroni correction (significance threshold, ), and the results did not survive this strict correction. No statistically significant associations were found in the exudative AMD group (data not shown).


ModelGenotype/alleleOR (95% CI) valueAIC

Early AMD
IL-9 rs1859430
CodominantGA vs. GG0.700 (0.507-0.966)0.0301000.541
AA vs. GG1.713 (0.857-3.424)0.128
DominantGA+AA vs. GG0.794 (0.585-1.077)0.137998.541
RecessiveAA vs. GA+GG1.926 (0.972-3.816)0.060997.109
OverdominantGA vs. GG+AA0.673 (0.490-0.925)0.015994.759
AdditiveA0.938 (0.731-1.203)0.6131000.499
IL-9 rs11741137
CodominantCT vs. CC0.734 (0.530-1.015)0.062997.863
TT vs. CC1.489 (0.646-3.431)0.350
DominantCT+TT vs. CC0.788 (0.577-1.077)0.135998.512
RecessiveTT vs. CT+CC1.635 (0.714-3.745)0.245999.381
OverdominantCT vs. CC+TT0.720 (0.522-0.994)0.046996.749
AdditiveT0.883 (0.675-1.156)0.365999.931

Atrophic AMD
IL-10 rs1800896
CodominantTC vs. TT1.023 (0.503-2.079)0.951321.969
CC vs. TT2.043 (0.938-4.450)0.072
DominantTC+CC vs. TT1.296 (0.670-2.505)0.441323.962
RecessiveCC vs. TC+TT2.013 (1.078-3.759)0.028319.973
OverdominantTC vs. TT+CC0.719 (0.408-1.266)0.253323.257
AdditiveC1.454 (0.967-2.187)0.072321.302

Adjusted for gender in early AMD and adjusted for age in atrophic AMD group. OR: odds ratio; CI: confidence interval; : significance level and Bonferroni corrected significance level when ; AIC: Akaike information criterion.

While it has been suggested that AMD pathogenesis can be differentiated by gender [14], we performed the SNP analysis in males and females separately and found that IL-9 rs11741137 (CC, CT, and TT), IL-9 rs2069885 (GG, GA, and AA), and IL-9 rs2069884 (GG, GT, and TT) genotypes were distributed statistically significantly between males with early AMD and control males: 73.3%, 20%, and 6.7 vs. 66.4%, 31.5%, and 2%, ; 73.3%, 20%, and 6.7 vs. 67.1%, 30.9%, and 2%, ; 73.3%, 20%, and 6.7 vs. 67.1%, 30.9%, and 2%, , respectively (Table 4). No statistically significant associations were found in the exudative or atrophic AMD groups and female group analysis (data not shown).


SNPGenotypes/allelesGroup value
Early AMD (), (%)Control (), (%)

rs11741137CC77 (73.3)99 (66.4)0.032
CT21 (20.0)47 (31.5)
TT7 (6.7)3 (2.0)
C175 (83.3)245 (82.2)0.743
T35 (13.3)53 (17.8)

rs2069885GG77 (73.3)100 (67.1)0.039
GA21 (20.0)46 (30.9)
AA7 (6.7)3 (2.0)
G175 (83.3)246 (82.6)0.818
A35 (13.3)52 (17.4)

rs2069884GG77 (73.3)100 (67.1)0.039
GT21 (20.0)46 (30.9)
TT7 (6.7)3 (2.0)
G175 (83.3)246 (82.6)0.818
T35 (13.3)52 (17.4)

: significance level and Bonferroni corrected significance level when .

Binomial logistic regression analysis revealed that IL-9 rs1859430 GA genotype was associated with 46 and 48% decreased odds of early AMD in males under the codominant and overdominant genetic models (; CI: 0.302-0.991; and ; CI: 0.292-0.948; , respectively). IL-9 rs11741137 CT genotype was associated with 46% decreased odds of early AMD in males (; CI: 0.301-0.979; ) under the codominant model (Table 5).


ModelGenotype/alleleOR (95% CI) valueAIC

IL-9 rs1859430
CodominantGA vs. GG0.547 (0.302-0.991)0.047342.864
AA vs. GG1.667 (0.54-5.010)0.363
DominantGA+AA vs. GG0.671 (0.390-1.155)0.150344.355
RecessiveAA vs. GA+GG1.966 (0.661-5.843)0.224342.961
OverdominantGA vs. GG+AA0.526 (0.292-0.948)0.033341.702
AdditiveA0.863 (0.562-1.327)1.327346.005

IL-9 rs11741137
CodominantCT vs. CC0.574 (0.317-1.041)0.068341.517
TT vs. CC3.000 (0.751-11.983)0.120
DominantCT+TT vs. CC0.720 (0.415-1.248)0.242345.071
RecessiveTT vs. CT+CC3.476 (0.878-13.769)0.076342.969
OverdominantCT vs. CC+TT0.543 (0.301-0.979)0.042342.175
AdditiveT0.929 (0.590-1.464)0.751346.357

Only two genotypes were determined. OR: odds ratio; CI: confidence interval; p: significance level and Bonferroni corrected significance level when ; AIC: Akaike information criterion.

None of the results survived strict Bonferroni correction (significance threshold, ).

3.3. Haplotype Association with the Predisposition to AMD Occurrence

Strong linkage disequilibrium between studied polymorphisms was observed (Table 6).


SNP1 (; )SNP2 (; )SNP3 (; )SNP4 (; )SNP5 (; )SNP6 (; )SNP7 (; )SNP8 (; )

SNP1 (; )0.9828; 0.83390.9167; 0.67520.9397; 0.68770.9401; 0.6922
SNP2 (; )0.8271; 0.63660.8436; 0.64190.8445; 0.6471
SNP3 (; )0.9942; 0.95790.9942; 0.9633
SNP4 (; )0.9995; 0.9932
SNP5 (; )
SNP6 (; )0.9997; 0.99940.9883; 0.2454
SNP7 (; )0.9883; 0.2454
SNP8 (; )

is the deviation between the expected haplotype frequency and the observed frequency [ scale: 0,1]. is squared correlation coefficient of the haplotype frequencies [ scale: 0,1]. SNP1: rs1859430; SNP2: rs2069870; SNP3: rs11741137; SNP4: rs2069885; SNP5: rs2069884; SNP6: rs1800871; SNP7: rs1800872; SNP8: rs1800896.

While the haplotype analyses identified many of their sets, any differences in the haplotype frequencies between the atrophic AMD and control groups were observed (Table 7). The results of the frequencies of haplotypes among patients with early AMD and controls have shown that haplotypes A-G-C-G-G and G-A-T-A-T of IL-9 SNPs (rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884) are associated with the decreased odds of early AMD occurrence (; 95% CI: 0.025-0.95; and ; 95% CI: 0.01-0.61; , respectively). The set of rare haplotypes was associated with the decreased odds of exudative AMD occurrence (; 95% CI: 0.015-092; ) (Table 7).


SNP1SNP2SNP3SNP4SNP5SNP6SNP7SNP8FrequencyOR (95% CI) value

Haplotype associations with early AMD
1GACGG0.77151
2AGTAT0.14680.76 (0.54-1.08)0.13
3AGCGG0.03350.49 (0.25-0.95)0.035
4AATAT0.0181.74 (0.72-4.22)0.22
5GATAT0.01080.08 (0.01-0.61)0.015
6AACGG0.01032.25 (0.66-7.66)0.19
7 (rare)0.0091.29 (0.32-5.21)0.72
8GGC0.45491
9GGT0.32751.13 (0.89-1.44)0.31
10ATT0.21661.00 (0.75-1.32)0.98
11 (rare)0.001<0.001 (-)1

Haplotype associations with exudative AMD
1GACGG0.77131
2AGTAT0.14870.96 (0.69-1.35)0.83
3AGCGG0.04080.99 (0.57-1.73)0.98
4AATAT0.01651.11 (0.46-2.66)0.82
5 (rare)0.02270.37 (0.15-0.92)0.033
6GGC0.47511
7GGT0.30260.87 (0.68-1.10)0.24
8ATT0.22050.94 (0.72-1.22)0.63
9 (rare)0.00180.34 (0.02-5.66)0.45

Haplotype associations with atrophic AMD
1GACGG0.75581
2AGTAT0.15181.25 (0.65-2.40)0.5
3AGCGG0.04532.34 (0.93-5.88)0.071
4GATAT0.0167<0.00 (-)1
5AATAT0.01621.05 (0.23-4.68)0.95
6 (rare)0.01420.55 (0.07-4.43)0.57
7GGC0.47581
8GGT0.30460.62 (0.38-1.02)0.06
9ATT0.2180.78 (0.47-1.29)0.33
10 (rare)0.0016<0.00 (-)1

Rare: pooled rare haplotypes; OR: odds ratio; CI: confidence interval; p: significance level when ; SNP1: rs1859430; SNP2: rs2069870; SNP3: rs11741137; SNP4: rs2069885; SNP5: rs2069884; SNP6: rs1800871; SNP7: rs1800872; SNP8: rs1800896.
3.4. IL-9 and IL-10 Serum Levels in the AMD and Control Groups

IL-9 and IL-10 serum levels were measured in patients with early AMD (), exudative AMD (), atrophic AMD (), and controls (). Subgroups for interleukin serum level measurements consisted of study subjects considering the age and gender distributions in subgroups. IL-9 levels did not reach the detection range, and it was not analyzed. IL-10 serum levels differed between study groups () (Figure 1). When comparing the IL-10 serum levels between every two groups, we found that IL-10 serum levels were lower in exudative AMD than in controls (8.0 (2.7) pg/ml vs. 8.8 (2.4) pg/ml, ) and also in patients with early AMD (8.0 (2.7) pg/ml vs. 9.2 (1.7) pg/ml, ) and atrophic AMD (8.0 pg/ml vs. 9.4 (1.5) pg/ml, ).

We also performed the IL-10 serum level and SNP association analysis and found that exudative AMD patients with IL-10 rs1800896 CT and TT genotypes had lower IL-10 serum concentrations than those with wild-type (CC) genotype: 7.2 (2.3) vs. 9.3 (1.4); (Table 8).


ModelEarly AMD (pg/ml), median (IQR) valueExudative AMD (pg/ml), median (IQR) valueAtrophic AMD (pg/ml), median (IQR) valueControl group (pg/ml), median (IQR) value

IL-10 rs1800871
DominantGA+AA vs. GG9.2 (15.8) vs. 9.1 (1.5)0.5718.6 (3.9) vs. 7.7 (2.6)0.3129.3 (1.1) vs. 9.5 (2.2)0.2308.7 (2.6) vs. 8.8 (3.9)0.442
RecessiveAA vs. GA+GG(-) vs. 9.2 (1.4)(-) vs. 7.9 (2.9)(-) vs. 9.4 (1.6)(-) vs. 8.8 (2.9)

IL-10 rs1800872
DominantGT+TT vs. GG9.2 (15.8) vs. 9.1 (1.5)0.5718.6 (3.9) vs. 7.7 (2.6)0.3129.3 (1.1) vs. 9.5 (2.2)0.2308.7 (2.6) vs. 8.8 (3.9)0.442
RecessiveTT vs. GT+GG(-) vs. 9.2 (1.4)(-) vs. 7.9 (2.9)(-) vs. 9.4 (1.6)(-) vs. 8.8 (2.9)

IL-10 rs1800896
DominantTC+CC vs. TT9.1 (1.8) vs. 9.3 (7.8)0.8007.2 (2.3) vs. 9.3 (1.4)0.0489.4 (2.2) vs. 9.3 (0.7)0.8008.8 (3.4) vs. 8.7 (-)0.573
RecessiveCC vs. TC+TT9.2 (-) vs. 9.1 (2.7)0.5466.7 (2.2) vs. 8.5 (2.5)0.0548.7 (1.5) vs. 9.5 (1.2)0.1538.7 (-) vs. 8.8 (2)0.958

Only two genotypes were determined.

4. Discussion

Our study is aimed at analyzing the associations between the immunogenetic markers IL-9 (rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884) and IL-10 (rs1800871, rs1800872, and rs1800896) polymorphisms and their haplotypes, serum IL-9 and IL-10 levels and the different AMD forms.

IL-9 belongs to the IL-2Rγc chain family and works as a pleiotropic cytokine in inflammatory processes [40]. T lymphocytes, or more specific Th2, were described as the primary source for the IL-9 production [41]. Nevertheless, further studies identified other cell types, including Th9, mast cells, innate lymphoid cells (ILCs), NK cells, and even Foxp3+ Tregs, as well as mucin-producing cells, and eosinophils could also produce IL-9 [4244]. Moreover, Dardalhon et al. have identified unique T cells that produce both IL-9 and IL-10, leading to tissue inflammation [45]. Previously, IL-9 was described as a growth factor for T cells and mast cells [46, 47]. It is known that IL-9 can promote the growth and function of the erythroid progenitor, fetal thymocyte, myeloid precursor cells, and human megakaryoblastic leukemic cell lines [48]. IL-9 behavior is regulated through the specific IL-9 receptor (IL9R, which is contained of two subunits: the alpha chain (IL-9Rα) and the common gamma chain receptor). IL-9 binds the IL-9Rα subunit and forms the IL-9R heterocomplex. Because of the lack of specific enzymatic activity, the JAK/STAT pathway needs to be activated, and JAK is the initiator of the following phosphorylation cascades [49]. Previous inflammation-associated studies were reviewed and showed the pathogenic role of IL-9 in inflammatory disease development [48]. On the other hand, Elyaman et al. have been suggested the diverse role of IL-9, including both a regulator of pathogenic and protective mechanisms of immune responses [50].

IL-9 is encoded by the IL-9 gene located on chromosome 5q31.1 [51]. Several IL-9 variants (rs31563, rs1859430, rs11741137, and rs2069885) have already been published and identified as potential biomarkers for atopic dermatitis, asthma and its severity, respiratory syncytial virus (RSV) infection, and pituitary adenoma [3035].

Namkung et al. reported that rs31563 (−4091G/A) at the IL-9 gene was associated with increased susceptibility to atopic dermatitis [34]. Another study revealed that IL-9 rs1859430 genotype frequencies were lower in asthma patients than in controls under the recessive GA+AA () and heterozygous GA () models. Also, those patients had significantly lower A-T (rs1859430-rs2066758) haplotype frequency () and higher G-T (rs1859430-rs2066758) haplotype frequency (). Moreover, they showed that rs1859430 AG genotype was associated with the higher IL-9 serum levels compared with other genotypes in the disease group (), and the rs2066758 CC genotype was linked to the partial pressure of carbon dioxide (PaCO2) () [35]. Two authors underlined the differences between gender groups in asthma and RSV infection development, considering the sex-dependent mechanisms. Aschard et al. showed that polysensitization (SPTQ) and forced expiratory volume in one second divided by height square (FEV(1)/H(2)) were associated with two IL-9 variants rs2069885 and rs2069882 ( and , respectively, after Bonferroni’s correction). This study underlines the importance of complex mechanisms, such as heterogeneity, according to sex and pleiotropy, to reveal the genes involved in asthma phenotypes [33]. Schuurhof et al. revealed that the major allele at rs2069885 was associated with increased susceptibility to severe RSV infection in boys’ and girls’ opposite associations. Furthermore, the haplotype T-T rs2069885 and rs1799962 was a risk marker for severe RSV bronchiolitis in girls [32]. One more study found that study subjects with the dominant genotype for these IL-9 polymorphisms (rs11741137, rs2069885, and rs1859430) were associated with a severe asthma exacerbation if exposed to increased dust mite levels ( to 0.03). It was even replicated it in another study () [52]. IL-9 rs1859430 G/A and A/A genotypes were also found to be associated with increased odds of having recurrent PA under the codominant ( and , respectively), dominant (), and recessive () genetic models [30].

Controversial results were observed in several studies as well, and they reported no significant associations between IL-9 promoter polymorphism A−345G and RSV bronchiolitis [52], T113M in IL-9 and atopic bronchial asthma [53], rs1859430 and rs2069868 and Graves’ disease [54], or IL-9 rs2069885 and allergic rhinitis in Iranian women [55]. Schürks et al. tried to show associations between IL-9 rs2069885 and inflammatory pathways among women with migraine, but results did not survive the corrections for multiple testing [56]. Also, IL-9 rs31563 C>T and rs31564 G>T were not associated with gastric cardiac adenocarcinoma and esophageal cancer in a Chinese population [57, 58].

According to the databases, any IL-9 SNPs were analyzed in AMD. Our study shows that IL-9 rs1859430 GA genotype and IL-9 rs11741137 CT genotypes were associated with decreased odds of early AMD. Unfortunately, in our study, we applied Bonferroni’s correction because of the multiple comparisons, and associations between study groups and SNPs in IL-9 did not survive this strict correction.

In further analysis, the same tendencies remained only in the male group. Even if these results did not survive Bonferroni’s correction, differences between male and female groups were observed as in previous studies [14, 32, 33]. Potentially different inflammation processes in men and women should be studied, considering the hormone role on molecular mechanisms in inflammation and response to inflammation, which may lead to opposite disease outcomes [59].

Also, we performed the haplotype analysis and identified the haplotypes A-G-C-G-G and G-A-T-A-T of IL-9 SNPs (rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884), which were associated with the decreased odds of early AMD ( and , respectively). The set of rare haplotypes was associated with the decreased odds of exudative AMD (), which may have a potential role in the IL-9-dependent inflammation process involved in AMD development.

In our study, the serum IL-9 levels were not determined because of the low detection rates. On the other hand, IL-9 was previously involved in several AMD studies. IL-9 cytokine in the aqueous humor was measured, but differences between neovascular AMD and the control groups were not found [60]. IL-9 was also measured in aqueous humor samples of neovascular AMD before the treatment by intravitreal drug injection and after, and compared with the control group, but the statistical analysis did not show any differences between study groups [61]. In another study, plasma and aqueous humor IL-9 levels between exudative AMD and the control groups were not reported because of the low detection rate [62]. Extremely low limits of detection of IL-9 in the aqueous fluid of patients with neovascular AMD were reported as well [63].

Contrarily, Lin et al. revealed that cytokine IL-9 was overexpressed in stimulated RPE cells, with a potential association with AMD development [23]. Unfortunately, no other studies, including IL-9 and AMD, were found. Otherwise, few diseases/conditions were reported, and elevated IL-9 levels were found in asthmatic patients, patients with allergic rhinitis and a peanut allergy, and those suffering from some autoimmune diseases [48].

IL-10 belongs to the IL-10 family, and as an anti-inflammatory cytokine, the IL-10 takes part in the regulation of the inflammatory response [64]. Macrophages are the primary source of IL-10. Still, other immune cells (monocytes, dendritic cells, B lymphocytes, T helper 1 (Th1) and Th2 lymphocytes, mast cells, NK cells, cytotoxic T cells, and granulocytes like neutrophils and eosinophils) can secrete this interleukin [65, 66]. As a pleiotropic cytokine, IL-10 inhibits the antigen-presenting cells via the inhibition of expression of major histocompatibility complex (MHC) class II molecules. It also suppresses the expression of IL-1, IL-6, IL-8, IL-12, and tumor necrosis factor-alpha (TNF-α). Furthermore, IL-10 promotes proliferation, activation, and differentiation and helps prevent cell apoptosis in B cells [27, 65]. The immunosuppressive IL-10 activity is mediated by the heterodimeric IL-10 receptors (IL-10R1 and IL-10R2). IL-10R1 primary ligates to IL-10 and dimerizes with IL10R2 leading to the activation of the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathway. Phosphorylated STAT3 molecules that enter the cell’s nucleus induce changes in the expression of immunomodulatory genes leading to the inhibition of the secreted proinflammatory cytokines and downstream immune response, and regulate the activity of growth factors, such as VEGF [67, 68]. The IL-10 level changes were reported as a significant pathophysiological modulator in many diseases and reviewed previously [27].

IL-10 and genetic variants of IL-10 were also included in our study. IL-10 is encoded by the IL-10 gene located on chromosome 1q32.1, and three most studied point mutations in IL-10 promoter -592 A/C (rs1800872), -819 C/T (rs1800871), and -1082G/A (rs1800896) were described as leading genetic variations for SNP association studies [37]. Our present study showed that the IL-10 rs1800896 CC genotype was associated with 2-fold increased odds of atrophic AMD (), but these results did not survive strict Bonferroni’s correction as well.

Shevchenko et al. reported similar results. They found a higher IL10-1082 GG genotype frequency in AMD patients than in the controls [69], while in another study, the associations of IL-10 -592 A/C, -819 C/T, and -1082G/A polymorphisms and late AMD were not determined [70]. Moreover, no more such studies were found, but these SNPs were associated with other conditions. For example, children with IL-10 -592 CC or -592 AA genotypes had a higher risk of hospitalization for RSV bronchiolitis than those with heterozygous genotype [52]. Also, IL-10 rs1800872 T>G polymorphism was associated with an increased risk of esophageal cancer in a Chinese population [58]. It was still not associated with gastric cardiac adenocarcinoma in the same population [57], suggesting further investigations for the IL-10 signaling pathway associations with cancer development.

Previous studies have also shown that the elevated IL-10 levels in the eye induce the alternative macrophage activation, which can be associated with choroidal neovascularization development [71, 72]. We also analyzed serum IL-10 levels and found that IL-10 serum levels were lower in exudative AMD than in controls (), and also in patients with early AMD () and atrophic AMD (). Similar results were found by the other researcher group, which revealed lower concentrations of IL-10 cytokine in the wet and dry AMD groups than in controls ( and ). Also, they determined that IL-10 levels were higher in wet AMD than in the dry AMD group () [73]. Opposite results were found when Subhi et al. revealed that patients with neovascular AMD had higher plasma levels of IL-10 compared to healthy controls (), and statistically significant results remained even after multivariate analysis (after adjusting for demographics, comorbidities, and lifestyle factors) IL-10 () [74]. Statistically, significantly elevated IL-10 serum levels in AMD patients were determined by Nassar et al. as well [75]. On the other hand, the expression of IL-10 did not differ between Tfh cells from AMD patients and non-AMD controls [76]. It is interesting that IL-10 levels in the aqueous humor did not differ between the neovascular AMD and control groups [6163]. Few other studies have not even determined IL-10 in plasma or aqueous humor samples of AMD patients [6163]. In contrast, the others showed that IL-10 levels do not differ between intraocular fluid and serum samples [77].

Moreover, we found that IL-10 levels in the exudative AMD group are associated with the minor allele T, and patients with exudative AMD carrying IL-10 rs1800896 CT and TT genotypes have lower IL-10 serum concentrations than those with wild-type (CC) genotype. These findings confirm the IL-10 promoter polymorphism (rs1800896) role on IL-10 level changes [37], which can be responsible for the immune response in exudative AMD development. It is important to highlight that IL-9 (rs1859430, rs2069870, rs11741137, rs2069885, and rs2069884) and IL-10 (rs1800871, rs1800872, and rs1800896) gene variants, as well as serum IL-9 and IL-10 levels, have never been studied in AMD, in the Lithuanian population, and our study was the first of its type. While a thorough medical examination of the study objects can be acknowledged as one of our study’s main strengths, we should declare that the relatively small sample size and the other risk factors that were not involved in our study fall into this study’s limitations.

5. Conclusions

In conclusion, inflammation is an underlying mechanism in AMD development. We have found lower IL-10 serum levels in patients with exudative AMD than healthy controls and early or atrophic AMD patients. A minor allele at IL-10 rs1800896 was associated with the lower IL-10 serum levels in the exudative AMD group. The haplotypes of IL-9 SNPs were also associated with the decreased odds of early and exudative AMD occurrence. Further studies will be needed to elucidate this regulatory pathway’s underlying mechanism and its association with AMD clinical symptoms.

Data Availability

Data will be provided in case a request is made by editors, reviewers, or scientists.

Conflicts of Interest

The authors declare no conflict of interest.

Authors’ Contributions

A.V. and L.K. are responsible for the conceptualization. A.V. and D.C. are responsible for the data curation. A.V. is responsible for the writing of the original draft preparation. A.V., D.C., R.Z., and R.L. are responsible for the methodology. A.V., D.C., and L.K. are responsible for the investigation. A.V. is responsible for the formal analysis. L.K. and R.Z. are responsible for the validation. R.L. is responsible for the supervision. R.L. is responsible for the writing—reviewing and editing.

Supplementary Materials

Table S1: genotype distribution in the control group using Hardy-Weinberg equilibrium. Seven SNPs were in HWE (), but rs2069870 did not fulfill the HWE requirements because there were observed only two genotypes. (Supplementary Materials)

References

  1. C. J. Thomas and K. Schroder, “Pattern recognition receptor function in neutrophils,” Trends in Immunology, vol. 34, no. 7, pp. 317–328, 2013. View at: Publisher Site | Google Scholar
  2. N. Singh, D. Baby, J. P. Rajguru, P. B. Patil, S. S. Thakkannavar, and V. B. Pujari, “Inflammation and cancer,” Annals of African Medicine, vol. 18, no. 3, pp. 121–126, 2019. View at: Publisher Site | Google Scholar
  3. A. O. Odegaard, D. R. J. Jacobs, O. A. Sanchez, D. C. J. Goff, A. P. Reiner, and M. D. Gross, “Oxidative stress, inflammation, endothelial dysfunction and incidence of type 2 diabetes,” Cardiovascular Diabetology, vol. 15, no. 1, 2016. View at: Publisher Site | Google Scholar
  4. T. Chitnis and H. L. Weiner, “CNS inflammation and neurodegeneration,” The Journal of Clinical Investigation, vol. 127, no. 10, pp. 3577–3587, 2017. View at: Publisher Site | Google Scholar
  5. D. H. Anderson, M. J. Radeke, N. B. Gallo et al., “The pivotal role of the complement system in aging and age-related macular degeneration: hypothesis re-visited,” Progress in Retinal and Eye Research, vol. 29, no. 2, pp. 95–112, 2010. View at: Publisher Site | Google Scholar
  6. W. Smith, J. Assink, R. Klein et al., “Risk factors for age-related macular degeneration: pooled findings from three continents,” Ophthalmology, vol. 108, no. 4, pp. 697–704, 2001. View at: Publisher Site | Google Scholar
  7. R. Klein, B. E. Klein, S. C. Jensen, and S. M. Meuer, “The five-year incidence and progression of age-related maculopathy: the Beaver Dam Eye Study,” Ophthalmology, vol. 104, no. 1, pp. 7–21, 1997. View at: Publisher Site | Google Scholar
  8. F. M. C. Medina, A. A. L. da Motta, W. Y. Takahashi et al., “Pharmacogenetic effect of complement factor H gene polymorphism in response to the initial intravitreal injection of bevacizumab for wet age-related macular degeneration,” Ophthalmic Research, vol. 54, no. 4, pp. 169–174, 2015. View at: Publisher Site | Google Scholar
  9. N. Parekh, “Association between dietary fat intake and age-related macular degeneration in the Carotenoids in Age-Related Eye Disease Study (CAREDS): an ancillary study of the Women’s Health Initiative,” Archives of Ophthalmology, vol. 127, no. 11, pp. 1483–1493, 2009. View at: Publisher Site | Google Scholar
  10. L. G. Fritsche, W. Igl, J. N. C. Bailey et al., “A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants,” Nature Genetics, vol. 48, no. 2, pp. 134–143, 2016. View at: Publisher Site | Google Scholar
  11. M. Zhang, N. Jiang, Y. Chu et al., “Dysregulated metabolic pathways in age-related macular degeneration,” Scientific Reports, vol. 10, no. 1, p. 2464, 2020. View at: Publisher Site | Google Scholar
  12. J. Rullo, P. M. Far, M. Quinn et al., “Local oral and nasal microbiome diversity in age-related macular degeneration,” Scientific Reports, vol. 10, no. 1, p. 3862, 2020. View at: Publisher Site | Google Scholar
  13. W. L. Wong, X. Su, X. Li et al., “Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis,” The Lancet Global Health, vol. 2, no. 2, pp. e106–e116, 2014. View at: Publisher Site | Google Scholar
  14. M. Sasaki, S. Harada, Y. Kawasaki et al., “Gender-specific association of early age-related macular degeneration with systemic and genetic factors in a Japanese population,” Scientific Reports, vol. 8, no. 1, p. 785, 2018. View at: Publisher Site | Google Scholar
  15. Age-Related Eye Disease Study Research Group, “The Age-Related Eye Disease Study system for classifying age-related macular degeneration from stereoscopic color fundus photographs: the Age-Related Eye Disease Study Report Number 6,” American Journal of Ophthalmology, vol. 132, no. 5, pp. 668–681, 2001. View at: Publisher Site | Google Scholar
  16. F. L. Ferris, M. D. Davis, T. E. Clemons, L.-Y. Lee, E. Y. Chew, and A. S. Lindblad, “A simplified severity scale for age-related macular degeneration: AREDS Report No. 18,” Archives of Ophthalmology, vol. 123, 2005. View at: Publisher Site | Google Scholar
  17. S. Ryan, C. Wilkinson, and A. Schachat, David Hinton CW. Retina, Elsevier, St Louis, 4th edition, 2006.
  18. J. W. Miller, “Age-Related Macular Degeneration Revisited - Piecing the Puzzle: The LXIX Edward Jackson Memorial Lecture,” American Journal of Ophthalmology, vol. 155, no. 1, pp. 1–35.e13, 2013. View at: Publisher Site | Google Scholar
  19. I. Bhutto and G. Lutty, “Understanding age-related macular degeneration (AMD): relationships between the photoreceptor/retinal pigment epithelium/Bruch’s membrane/choriocapillaris complex,” Molecular Aspects of Medicine, vol. 33, no. 4, pp. 295–317, 2012. View at: Publisher Site | Google Scholar
  20. F. Parmeggiani, M. R. Romano, C. Costagliola et al., “Mechanism of inflammation in age-related macular degeneration,” Mediators of Inflammation, vol. 2012, Article ID 546786, 16 pages, 2012. View at: Publisher Site | Google Scholar
  21. H. Xu, M. Chen, and J. V. Forrester, “Para-inflammation in the aging retina,” Progress in Retinal and Eye Research, vol. 28, no. 5, pp. 348–368, 2009. View at: Publisher Site | Google Scholar
  22. J. T. Handa, N. Verzijl, H. Matsunaga et al., “Increase in the advanced glycation end product pentosidine in Bruch’s membrane with age,” Investigative Ophthalmology & Visual Science, vol. 40, no. 3, pp. 775–779, 1999. View at: Google Scholar
  23. T. Lin, G. B. Walker, K. Kurji et al., “Parainflammation associated with advanced glycation endproduct stimulation of RPE in vitro: implications for age-related degenerative diseases of the eye,” Cytokine, vol. 62, no. 3, pp. 369–381, 2013. View at: Publisher Site | Google Scholar
  24. I. A. Bhutto, D. S. McLeod, T. Hasegawa et al., “Pigment epithelium-derived factor (PEDF) and vascular endothelial growth factor (VEGF) in aged human choroid and eyes with age-related macular degeneration,” Experimental Eye Research, vol. 82, no. 1, pp. 99–110, 2006. View at: Publisher Site | Google Scholar
  25. A. Das and P. G. McGuire, “Retinal and choroidal angiogenesis: pathophysiology and strategies for inhibition,” Progress in Retinal and Eye Research, vol. 22, no. 6, pp. 721–748, 2003. View at: Publisher Site | Google Scholar
  26. H. R. Coleman, C.-C. Chan, F. L. Ferris 3rd, and E. Y. Chew, “Age-related macular degeneration,” Lancet (London, England), vol. 372, pp. 1835–1845, 2008. View at: Publisher Site | Google Scholar
  27. S. S. Iyer and G. Cheng, “Role of interleukin 10 transcriptional regulation in inflammation and autoimmune disease,” Critical Reviews in Immunology, vol. 32, no. 1, pp. 23–63, 2012. View at: Publisher Site | Google Scholar
  28. S. B. Early, P. Huyett, K. Brown-Steinke, L. Borish, and J. W. Steinke, “Functional analysis of −351 interleukin-9 promoter polymorphism reveals an activator controlled by NF-κB,” Genes and Immunity, vol. 10, no. 4, pp. 341–349, 2009. View at: Publisher Site | Google Scholar
  29. R. Liutkeviciene, A. Vilkeviciute, G. Streleckiene, L. Kriauciuniene, R. Chaleckis, and V. P. Deltuva, “Associations of cholesteryl ester transfer protein (CETP) gene variants with predisposition to age-related macular degeneration,” Gene, vol. 636, pp. 30–35, 2017. View at: Publisher Site | Google Scholar
  30. T. Mickevicius, A. Vilkeviciute, B. Glebauskiene, L. Kriauciuniene, and R. Liutkeviciene, “Do TRIB1 and IL-9 gene polymorphisms impact the development and manifestation of pituitary adenoma?” In Vivo, vol. 34, pp. 2499–2505, 2020. View at: Publisher Site | Google Scholar
  31. J. E. Sordillo, R. Kelly, S. Bunyavanich et al., “Genome-wide expression profiles identify potential targets for gene-environment interactions in asthma severity,” The Journal of Allergy and Clinical Immunology, vol. 136, 2015. View at: Publisher Site | Google Scholar
  32. A. Schuurhof, L. Bont, C. L. E. Siezen et al., “Interleukin-9 polymorphism in infants with respiratory syncytial virus infection: an opposite effect in boys and girls,” Pediatric Pulmonology, vol. 45, no. 6, pp. 608–613, 2010. View at: Publisher Site | Google Scholar
  33. H. Aschard, on behalf of the EGEA cooperative group, E. Bouzigon et al., “Sex-specific effect of IL9 polymorphisms on lung function and polysensitization,” Genes and Immunity, vol. 10, no. 6, pp. 559–565, 2009. View at: Publisher Site | Google Scholar
  34. J.-H. Namkung, J.-E. Lee, E. Kim et al., “An association between IL-9 and IL-9 receptor gene polymorphisms and atopic dermatitis in a Korean population,” Journal of Dermatological Science, vol. 62, pp. 16–21, 2011. View at: Publisher Site | Google Scholar
  35. L.-X. Chen, C.-M. Xu, F. Gao, M.-F. Zhu, M.-J. Xu, and J.-R. Zhang, “Associations of IL-18 and IL-9 expressions and gene polymorphisms with asthma,” European Review for Medical and Pharmacological Sciences, vol. 24, pp. 6931–6938, 2020. View at: Publisher Site | Google Scholar
  36. Y. Zhang, J. Li, C. Wang, and L. Zhang, “Association between the interaction of key genes involved in effector T-cell pathways and susceptibility to develop allergic rhinitis: a population-based case-control association study,” PLoS One, vol. 10, no. 7, article e0131248, 2015. View at: Publisher Site | Google Scholar
  37. D. M. Turner, D. M. Williams, D. Sankaran, M. Lazarus, P. J. Sinnott, and I. V. Hutchinson, “An investigation of polymorphism in the interleukin-10 gene promoter,” European Journal of Immunogenetics : Official Journal of the British Society for Histocompatibility and Immunogenetics, vol. 24, no. 1, pp. 1–8, 1997. View at: Publisher Site | Google Scholar
  38. A. Vilkeviciute, N. Bastikaityte, R. Mockute et al., “The role of SNPs in IL1RL1 and IL1RAP genes in age-related macular degeneration development and treatment efficacy,” In Vivo, vol. 34, no. 5, pp. 2443–2451, 2020. View at: Publisher Site | Google Scholar
  39. X. Solé, E. Guinó, J. Valls, R. Iniesta, and V. Moreno, “SNPStats: a web tool for the analysis of association studies,” Bioinformatics (Oxford, England), vol. 22, pp. 1928-1929, 2006. View at: Publisher Site | Google Scholar
  40. X. C. Li, A. D. Schachter, M. S. Zand et al., “Differential expression of T-cell growth factors in rejecting murine islet and human renal allografts,” Transplantation, vol. 66, no. 2, pp. 265–268, 1998. View at: Publisher Site | Google Scholar
  41. E. Schmitt, R. van Brandwijk, J. van Snick, B. Siebold, and E. Rüde, “TCGF III/P40 is produced by naive murine CD4+ T cells but is not a general T cell growth factor,” European Journal of Immunology, vol. 19, no. 11, pp. 2167–2170, 1989. View at: Publisher Site | Google Scholar
  42. S. Koch, N. Sopel, and S. Finotto, “Th9 and other IL-9-producing cells in allergic asthma,” Seminars in Immunopathology, vol. 39, no. 1, pp. 55–68, 2017. View at: Publisher Site | Google Scholar
  43. R. J. Noelle and E. C. Nowak, “Cellular sources and immune functions of interleukin-9,” Nature Reviews Immunology, vol. 10, no. 10, pp. 683–687, 2010. View at: Publisher Site | Google Scholar
  44. X. Xiao, S. Balasubramanian, W. Liu et al., “OX40 signaling favors the induction of TH9 cells and airway inflammation,” Nature Immunology, vol. 13, no. 10, pp. 981–990, 2012. View at: Publisher Site | Google Scholar
  45. V. Dardalhon, A. Awasthi, H. Kwon et al., “IL-4 inhibits TGF-beta-induced Foxp3+ T cells and, together with TGF-beta, generates IL-9+ IL-10+ Foxp3(-) effector T cells,” Nature Immunology, vol. 9, no. 12, pp. 1347–1355, 2008. View at: Publisher Site | Google Scholar
  46. L. Hültner, C. Druez, J. Moeller et al., “Mast cell growth-enhancing activity (MEA) is structurally related and functionally identical to the novel mouse T cell growth factor P40/TCGFIII (interleukin 9),” European Journal of Immunology, vol. 20, no. 6, pp. 1413–1416, 1990. View at: Publisher Site | Google Scholar
  47. C. Uyttenhove, R. J. Simpson, and J. van Snick, “Functional and structural characterization of P40, a mouse glycoprotein with T-cell growth factor activity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 85, no. 18, pp. 6934–6938, 1988. View at: Publisher Site | Google Scholar
  48. S. Chakraborty, K. F. Kubatzky, and D. K. Mitra, “An update on interleukin-9: from its cellular source and signal transduction to its role in immunopathogenesis,” International Journal of Molecular Sciences, vol. 20, no. 9, p. 2113, 2019. View at: Publisher Site | Google Scholar
  49. L. Knoops and J.-C. Renauld, “IL-9 and its receptor: from signal transduction to tumorigenesis,” Growth Factors (Chur, Switzerland), vol. 22, no. 4, pp. 207–215, 2004. View at: Publisher Site | Google Scholar
  50. W. Elyaman, E. M. Bradshaw, C. Uyttenhove et al., “IL-9 induces differentiation of TH17 cells and enhances function of FoxP3+ natural regulatory T cells,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 31, pp. 12885–12890, 2009. View at: Publisher Site | Google Scholar
  51. M. M. Le Beau, R. Espinosa, W. L. Neuman et al., “Cytogenetic and molecular delineation of the smallest commonly deleted region of chromosome 5 in malignant myeloid diseases,” Proceedings of the National Academy of Sciences of the United States of America, vol. 90, no. 12, pp. 5484–5488, 1993. View at: Publisher Site | Google Scholar
  52. B. Hoebee, L. Bont, E. Rietveld et al., “Influence of promoter variants of interleukin-10, interleukin-9, and tumor necrosis factor-alpha genes on respiratory syncytial virus bronchiolitis,” The Journal of Infectious Diseases, vol. 189, no. 2, pp. 239–247, 2004. View at: Publisher Site | Google Scholar
  53. M. B. Freĭdin, V. P. Puzyrev, L. M. Ogorodova, O. S. Kobiakova, and I. M. Kulmanakova, “Polymorphism of interleukins and interleukin receptor genes: population distribution and association with atopic bronchial asthma,” Genetika, vol. 38, no. 12, pp. 1710–1718, 2002. View at: Google Scholar
  54. W. Zhu, N. Liu, Y. Zhao, H. Jia, B. Cui, and G. Ning, “Association analysis of polymorphisms in IL-3, IL-4, IL-5, IL-9, and IL-13 with Graves’ disease,” Journal of Endocrinological Investigation, vol. 33, no. 10, pp. 751–755, 2010. View at: Publisher Site | Google Scholar
  55. F. Fatahi, A. Chaleshtori, K. G. Samani et al., “Assessment of the effects of IL9, IL9R, IL17A, and IL17F gene polymorphisms on women with allergic rhinitis in Shahrekord, Iran,” Annals of Medical and Health Sciences Research, vol. 6, no. 4, pp. 216–223, 2016. View at: Publisher Site | Google Scholar
  56. M. Schürks, T. Kurth, J. E. Buring, and R. Y. L. Zee, “A candidate gene association study of 77 polymorphisms in migraine,” The Journal of Pain : Official Journal of the American Pain Society, vol. 10, no. 7, pp. 759–766, 2009. View at: Publisher Site | Google Scholar
  57. J. Yin, X. Wang, J. Wei et al., “Interleukin 12Brs3212227 T > G polymorphism was associated with an increased risk of gastric cardiac adenocarcinoma in a Chinese population,” Diseases of the Esophagus : Official Journal of the International Society for Diseases of the Esophagus, vol. 28, no. 3, pp. 291–298, 2015. View at: Publisher Site | Google Scholar
  58. J.-M. Sun, Q. Li, H.-Y. Gu et al., “Interleukin 10 rs1800872 T>G polymorphism was associated with an increased risk of esophageal cancer in a Chinese population,” Asian Pacific Journal of Cancer Prevention : APJCP, vol. 14, no. 6, pp. 3443–3447, 2013. View at: Publisher Site | Google Scholar
  59. R. Lauretta, M. Sansone, A. Sansone, F. Romanelli, and M. Appetecchia, “Gender in endocrine diseases: role of sex gonadal hormones,” International Journal of Endocrinology, vol. 2018, Article ID 4847376, 11 pages, 2018. View at: Publisher Site | Google Scholar
  60. H. Zhou, X. Zhao, M. Yuan, and Y. Chen, “Comparison of cytokine levels in the aqueous humor of polypoidal choroidal vasculopathy and neovascular age-related macular degeneration patients,” BMC Ophthalmology, vol. 20, no. 1, p. 15, 2020. View at: Publisher Site | Google Scholar
  61. T. Sato, M. Takeuchi, Y. Karasawa, T. Enoki, and M. Ito, “Intraocular inflammatory cytokines in patients with neovascular age-related macular degeneration before and after initiation of intravitreal injection of anti-VEGF inhibitor,” Scientific Reports, vol. 8, no. 1, p. 1098, 2018. View at: Publisher Site | Google Scholar
  62. R. Agrawal, P. K. Balne, X. Wei et al., “Cytokine profiling in patients with exudative age-related macular degeneration and polypoidal choroidal vasculopathy,” Investigative Ophthalmology & Visual Science, vol. 60, no. 1, pp. 376–382, 2019. View at: Publisher Site | Google Scholar
  63. P. Pongsachareonnont, M. Y. K. Mak, C. P. Hurst, and W.-C. Lam, “Neovascular age-related macular degeneration: intraocular inflammatory cytokines in the poor responder to ranibizumab treatment,” Clinical Ophthalmology (Auckland, NZ), vol. 12, pp. 1877–1885, 2018. View at: Publisher Site | Google Scholar
  64. T. A. Hamilton, Y. Ohmori, and J. Tebo, “Regulation of chemokine expression by antiinflammatory cytokines,” Immunologic Research, vol. 25, no. 3, pp. 229–246, 2002. View at: Publisher Site | Google Scholar
  65. J. Trifunović, L. Miller, Ž. Debeljak, and V. Horvat, “Pathologic patterns of interleukin 10 expression--a review,” Biochemia Medica, vol. 25, no. 1, pp. 36–48, 2015. View at: Publisher Site | Google Scholar
  66. W. Ouyang, S. Rutz, N. K. Crellin, P. A. Valdez, and S. G. Hymowitz, “Regulation and functions of the IL-10 family of cytokines in inflammation and disease,” Annual Review of Immunology, vol. 29, no. 1, pp. 71–109, 2011. View at: Publisher Site | Google Scholar
  67. M. Wills-Karp, A. Nathan, K. Page, and C. L. Karp, “New insights into innate immune mechanisms underlying allergenicity,” Mucosal Immunology, vol. 3, no. 2, pp. 104–110, 2010. View at: Publisher Site | Google Scholar
  68. P. Gao, N. Niu, T. Wei et al., “The roles of signal transducer and activator of transcription factor 3 in tumor angiogenesis,” Oncotarget, vol. 8, no. 40, pp. 69139–69161, 2017. View at: Publisher Site | Google Scholar
  69. A. V. Shevchenko, V. F. Prokofev, V. I. Konenkov et al., “Cytokine gene polymorphisms in patients with age-related macular degeneration,” Vestnik Oftalmologii, vol. 132, no. 2, pp. 8–13, 2016. View at: Publisher Site | Google Scholar
  70. Y.-Y. Tsai, J.-M. Lin, L. Wan et al., “Interleukin gene polymorphisms in age-related macular degeneration,” Visual Science, vol. 49, no. 2, pp. 693–698, 2008. View at: Publisher Site | Google Scholar
  71. J. Kelly, A. Ali Khan, J. Yin, T. A. Ferguson, and R. S. Apte, “Senescence regulates macrophage activation and angiogenic fate at sites of tissue injury in mice,” The Journal of Clinical Investigation, vol. 117, no. 11, pp. 3421–3426, 2007. View at: Publisher Site | Google Scholar
  72. L. He and A. G. Marneros, “Macrophages are essential for the early wound healing response and the formation of a fibrovascular scar,” The American Journal of Pathology, vol. 182, no. 6, pp. 2407–2417, 2013. View at: Publisher Site | Google Scholar
  73. Z. Litwińska, A. Sobuś, K. Łuczkowska et al., “The interplay between systemic inflammatory factors and microRNAs in age-related macular degeneration,” Frontiers in Aging Neuroscience, vol. 11, p. 286, 2019. View at: Publisher Site | Google Scholar
  74. Y. Subhi, M. Krogh Nielsen, C. R. Molbech et al., “Plasma markers of chronic low-grade inflammation in polypoidal choroidal vasculopathy and neovascular age-related macular degeneration,” Acta Ophthalmologica, vol. 97, no. 1, pp. 99–106, 2019. View at: Publisher Site | Google Scholar
  75. K. Nassar, S. Grisanti, E. Elfar, J. Lüke, M. Lüke, and S. Grisanti, “Serum cytokines as biomarkers for age-related macular degeneration,” Graefe’s Archive for Clinical and Experimental Ophthalmology, vol. 253, pp. 699–704, 2015. View at: Publisher Site | Google Scholar
  76. Q. Wu, B. Liu, L. Yuan et al., “Dysregulations of follicular helper T cells through IL-21 pathway in age-related macular degeneration,” Molecular Immunology, vol. 114, pp. 243–250, 2019. View at: Publisher Site | Google Scholar
  77. J. C. ten Berge, Z. Fazil, L. I. Born et al., “Intraocular cytokine profile and autoimmune reactions in retinitis pigmentosa, age-related macular degeneration, glaucoma and cataract,” Acta Ophthalmologica, vol. 97, no. 2, pp. 185–192, 2019. View at: Publisher Site | Google Scholar

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