The age-standardized incidence rate for gastric cancer is estimated to be 11.1% worldwide and 39.1% for Ardabil province in northwest Iran.

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Abstract​

Introduction​

The age-standardized incidence rate for gastric cancer is estimated to be 11.1% worldwide and 39.1% for Ardabil province in northwest Iran. Single nucleotide polymorphisms (SNPs) occur in coding and non-coding regions, contributing to cancer susceptibility. To identify SNPs predisposing individuals to gastric cancer in this region, we compared 263 variants between the Ardabil population and other populations.

Materials and methods​

Whole exome sequencing was used to determine the distribution of variants in the genomic DNA of 150 volunteers (aged < 35 years) from the general population of Ardabil. We compared allele frequencies with databases such as Iranome, Alfa, GnomAD, and 1000G, and statistically analyzed their correlation with age-standardized incidence rates (ASRs) for gastric cancer in related populations using the Pearson correlation test. Some findings were validated using Sanger-based PCR-Sequencing. We determined the frequency of seventeen variants among 150 individuals with gastric cancer and 150 healthy volunteers (matched for age and sex) as the control group.

 

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Results​

Nineteen variants, including rs10061133, rs1050631, rs12220909, rs12983273, rs1695, rs2274223, rs2292832, rs2294008, rs2505901, rs2976391, rs33927012, rs3744037, rs3745469, rs4789936, rs4986790, rs4986791, rs6194, rs63750447, and rs6505162, were found to be significantly different between the general population of Ardabil and other populations. Among them, the variants rs1050631, rs12983273, rs1695, rs2274223, rs2292832, rs2505901, rs33927012, rs374569, and rs6505162 showed significant differences between the cases and controls.

Discussion​

In this study, 17 variants appeared to be involved in the etiology of the high frequency of gastric cancer in the Ardabil population. Some of the observed differences were consistent with previous case–control and meta-analysis reports from various parts of the world. These findings motivate further cohort investigations in this population. Ultimately, identifying prognostic factors can help diagnose individuals predisposed to gastric cancer in this population.

 

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Introduction​

Gastric cancer begins with the uncontrolled proliferation of cells in the stomach. Despite a decline in incidence, it remains one of the most common types of cancer worldwide. According to GLOBOCAN 2020, gastric cancer ranks fifth in incidence at 5.6%. However, it is the fourth leading cause of cancer deaths globally. This type of cancer is more common in males, ranking fourth among males. However, it is less significant among common cancers in women. Out of the 1,089,103 new cases of gastric cancer, 75.3% (819,944 cases) occurred in the Asian population. Additionally, the Asian population accounted for 74.8% of the mortality cases. The age-standardized incidence rate (ASR) for gastric cancer was estimated to be 11.1% worldwide. Eastern Asia, with the highest level of incidence rate, had an ASR of 22.4. Males and females in this area had ASRs of 32.5 and 13.2, respectively [1].
Ardabil province is located in the northwest of Iran. Based on an ASR of 49.1 for males and 25.4 for females in this area, compared to the Korean Republic (39.7 for males and 17.6 for females), its population is among the highest prevalence population affected by gastric cancer [2].
Among the subtypes of gastric cancer, the cardia type has been shown to be significantly higher in the Ardabil region compared to some European countries, the USA, Japan, and Korea. The highest incidence of gastric cancer, especially the cardia type, in the Ardabil region provides an exceptional opportunity to investigate its etiology [3].
Through genome-wide association studies (GWAS), more than 430 cancer-associated loci have been identified [4]. Multiple GWAS have been conducted for gastric cancer, leading to the determination of many cancer-associated loci. The SNPs associated with cancer susceptibility are located in coding or non-coding regions of the genome. Synonymous and non-synonymous mutations are two subtypes of coding SNPs [5].
Despite not affecting the amino acid sequence, synonymous variants may change the expression level and function of the gene product through post-transcriptional modification, translation rate stability of mRNA, failure of splicing regulatory proteins to interact with some exons, affecting the kinetics of translation, followed by slowing down the rate of protein synthesis and/or modification, and ultimately altering the pause site, which may result in a different conformation of the protein. Non-coding variants are located in intervening and intergenic sequences, accounting for more than 90% of interindividual variations. Depending on the variant's location, it may be involved in the regulation of gene expression by harboring response elements such as promoters and enhancers, as well as post-transcriptional and translational processing [6].
Additionally, changes in epigenetic modification and chromatin structure caused by non-coding variants can alter the target gene expression level. Variants in the 3' UTR of genes can modulate the interactions between mRNA and related microRNAs, as well as polyadenylation, and can impact translation efficiency and/or mRNA stability [7].
MicroRNAs are small (18–20 nucleotide) non-coding RNAs that regulate mRNA translation by directly binding to their 3'-UTR. This regulation is managed through cleavage of the mRNA transcript and/or repression of translation, depending on the complementarity between the miRNA and its targeted mRNA. Therefore, SNPs in the sequence and/or 3'-UTR of the mRNA transcript can be valuable markers for predicting cancer susceptibility. SNPs in miRNAs and miRNA binding sites play critical roles as cancer risk biomarkers. For example, the miR-453 binding site in the ESR1 gene, the miR-638 binding site in the BRCA1 gene, and the miR-628-5p binding site in the TGFBR1 gene are important in breast cancer. Variants such as rs3783553 in hepatocellular carcinoma create new binding sites for miR-122 and miR-378 in the IL1A gene. There is also a relationship between SNPs within miRNA binding sites of the CD886, INSR, RPA2, and GTF2H1 genes and colorectal cancer. Furthermore, certain SNPs in the 3'-UTR of the MYCL1 and NBS1 genes are prognostic biomarkers in lung cancer, as well as breast, ovarian, and bladder cancers, while also serving as predictive biomarkers in bladder cancer (for response to radiotherapy), prostate cancer (for response to ADT), and response to Methotrexate and Cisplatin. SNPs in the seed sequence of miRNAs can also affect their processing or binding. Reported variants such as rs2910164 in miR-146a, rs3746444 in miR-499, rs12975333 in miR-125a, rs34059726 in miR-124, and rs11614913 in miR-196-a2 indicate an association between miRNA SNPs and cancer risk [8, 9].
In this study, we compared the frequency of 263 variants in coding and non-coding sequences between populations based on previous case–control, meta-analysis, and GWAS reports. The aim of this research was to identify variants that could be considered as predictive values for susceptibility to gastric cancer in the Ardabil population.

 

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Results​

Significant differences of allele distribution among different populations​

For the 260 variants selected to be correlated with gastric carcinogenesis through a literature review, allele frequencies were obtained from the whole exome sequencing (WES) results of the general population group (Additional file 2: Table S2).
Comparison of these results with frequencies from genomic databases such as Iranome, Alfa, 1000G, ExAC, and gnomAD, for Iran, Europe, and the world, revealed considerable differences. These variant frequencies were statistically analyzed using the Pearson correlation test and scatter plots, based on their reported age-standardized rates (ASR). Table 1 and Additional file 4: Fig. S1 display the significant differences (P < 0.05) and their corresponding scatter plots. The variants that showed significant differences were rs10061133, rs1050631, rs12220909, rs12983273, rs1695, rs2274223, rs2292832, rs2294008, rs2505901, rs2976391, rs33927012, rs3744037, rs3745469, rs4789936, rs4986790, rs4986791, rs6194, rs63750447, and rs6505162.

 

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Table 1 Statistical association between the variant frequencies in Ardabil population comparing Iran, Europe, and World data, based on their reported Age-Standardized Rates (ASR for Ardabil: 39.1, Iran: 16.6, Europe: 13.7, and World: 11.1)​

From: Genomic susceptibility to gastric cancer in Northwest Iran: population-based and case–control studies

Variant	Ardabil*	Iran	Europe	World	Pearson Cor.**	P Value1	Pearson Cor.***	P Value2
rs10061133	0.13	0.127	0.097	0.091	0.741	0.259	0.998	0.038
rs10069690	0.127	0.13	0.27	0.26	− 0.716	0.284	− 0.987	0.101
rs1044165	0.077	0.07	0.14	0.13	− 0.637	0.363	− 0.970	0.156
rs1047768	0.46	0.52	0.59	0.57	− 0.912	0.088	− 0.974	0.145
rs1050631	0.27	0.33	0.36	0.35	− 0.973	0.027	− 0.983	0.118
rs10509577	0.01	0.01	0.07	0.06	− 0.693	0.307	− 0.968	0.161
rs1051740	0.29	0.24	0.3	0.3	0.020	0.980	− 0.996	0.054
rs10519613	0.163	0.14	0.1	0.11	0.878	0.122	0.970	0.156
rs1052133	0.3	0.31	0.22	0.22	0.633	0.367	0.996	0.054
rs1052536	0.35	0.35	0.46	0.41	− 0.639	0.307	− 0.931	0.238
rs1052555	0.36	0.36	0.33	0.31	0.638	0.362	0.875	0.322
rs1059394	0.49	0.48	0.31	0.34	0.722	0.278	0.968	0.161
rs1061302	0.37	0.4	0.31	0.31	0.473	0.527	0.996	0.054
rs11134527	0.25	0.36	0.26	0.25	− 0.209	0.791	− 0.581	0.605
rs11170877	0.08	0.08	0.1	0.11	− 0.658	0.342	− 0.909	0.274
rs1143633	0.28	0.26	0.35	0.35	− 0.559	0.441	− 0.996	0.054
rs11797	0.33	0.38	0.55	0.58	− 0.803	0.197	− 0.979	0.132
rs12220909	0.003	0.01	0.0009	0.0007	0.057	0.943	1.0	0.004
rs1229984	0.75	0.81	0.96	0.94	− 0.848	0.152	− 0.983	0.117
rs12691693	0.64	0.54	0.61	0.59	0.561	0.439	0.875	0.322
rs12983273	0.107	0.136	0.138	0.136	− 0.983	0.017	− 0.990	0.090
rs12983508	0.1	0.11	0.17	0.17	− 0.768	0.232	− 0.996	0.054
rs138978736	0	0.0012	0.00075	0.00064	− 0.756	0.26	− 0.999	0.148
rs1562313	0.18	0.21	0.2	0.2	− 0.855	0.145	− 0.996	0.054
rs1695	0.297	0.319	0.326	0.327	− 0.994	0.006	− 0.998	0.035
rs16999593	0.013	0.007	0.0003	0.002	0.918	0.082	0.978	0.132
rs17276588	0.047	0.03	0.029	0.041	0.665	0.335	0.689	0.516
rs1799950	0.1	0.05	0.07	0.065	0.816	0.184	0.974	0.146
rs1800469	0.52	0.58	0.68	0.67	− 0.882	0.118	− 0.990	0.089
rs1800668	0.37	0.33	0.31	0.28	0.868	0.132	0.909	0.274
rs1801394	0.4	0.45	0.55	0.52	− 0.858	0.142	− 0.959	0.183
rs1870134	0.02	0.0187	0.00369	0.00496	0.746	0.255	0.999	0.106
rs1884444	0.497	0.54	0.53	0.53	− 0.914	0.086	− 0.996	0.054
rs2010963	0.58	0.63	0.68	0.68	− 0.933	0.067	− 0.996	0.054
rs2066702	0	0.004	0.002	0.01	− 0.715	0.285	− 0.725	0.484
rs2066981	0.41	0.42	0.48	0.47	− 0.771	0.229	− 0.974	0.146
rs2069763	0.22	0.23	0.33	0.32	− 0.750	0.250	− 0.984	0.114
rs2070600	0.007	0.02	0.04	0.04	− 0.890	0.110	− 0.996	0.054
rs2074570	0.01	0.05	0.04	0.056	− 0.888	0.112	− 0.902	0.284
rs2075570	0.38	0.43	0.5	0.51	− 0.894	0.106	− 0.986	0.106
rs217727	0.13	0.13	0.19	0.19	− 0.694	0.306	− 0.996	0.054
rs2228570	0.74	0.75	0.61	0.61	0.656	0.344	0.996	0.054
rs2257082	0.19	0.22	0.27	0.27	− 0.882	0.118	− 0.996	0.054
rs2274084	0.027	0.02	0.002	0.01	0.806	0.194	0.915	0.264
rs2274223	0.42	0.36	0.32	0.32	0.964	0.036	0.996	0.054
rs2274976	0.047	0.037	0.044	0.046	0.341	0.659	0.689	0.516
rs2292832	0.51	0.64	0.7	0.7	− 0.983	0.017	− 0.996	0.054
rs2294008	0.4	0.41	0.45	0.45	− 0.964	0.323	− 0.996	0.254
rs2296147	0.34	0.41	0.48	0.45	− 0.916	0.084	− 0.959	0.184
rs2305158	0.2	0.23	0.23	0.22	− 0.866	0.134	− 0.866	0.134
rs2505901	0.32	0.45	0.5	0.49	− 0.986	0.014	− 0.991	0.085
rs2839698	0.39	0.45	0.51	0.45	− 0.803	0.197	− 0.814	0.395
rs2920297	0.35	0.37	0.46	0.45	− 0.796	0.204	− 0.984	0.114
rs2976391	0.57	0.51	0.46	0.45	0.944	0.056	1	0.006
rs2976394	0.37	0.41	0.46	0.46	− 0.912	0.088	− 0.996	0.054
rs3171425	0.5	0.55	0.59	0.57	− 0.931	0.069	− 0.956	0.189
rs33927012	0.05	0.02	0.01	0.01	0.992	0.008	0.996	0.054
rs3660	0.29	0.37	0.52	0.51	− 0.869	0.131	− 0.992	0.078
rs3730089	0.12	0.13	0.16	0.17	− 0.793	0.207	− 0.959	0.183
rs3732183	0.21	0.23	0.27	0.3	− 0.832	0.168	− 0.972	0.151
rs3738590	0.24	0.24	0.26	0.26	− 0.694	0.306	− 0.996	0.054
rs3741216	0.02	0.04	0.03	0.04	− 0.849	0.151	− 0.910	0.272
rs3741219	0.37	0.46	0.5	0.45	− 0.886	0.114	− 0.883	0.311
rs3744037	0.2	0.166	0.163	0.167	0.976	0.024	0.983	0.116
rs3745469	0.24	0.17	0.1	0.09	0.930	0.070	1.0	0.016
rs3762272	0.08	0.06	0.02	0.03	0.891	0.137	0.998	0.161
rs3764880	0.43	0.34	0.26	0.29	0.932	0.068	0.969	0.159
rs3765524	0.41	0.35	0.29	0.3	0.932	0.068	0.987	0.101
rs3804100	0.14	0.14	0.07	0.07	0.694	0.306	0.996	0.054
rs3810366	0.54	0.52	0.3	0.3	0.737	0.263	0.996	0.054
rs3825569	0.65	0.55	0.63	0.62	0.427	0.573	0.972	0.151
rs4072037	0.42	0.45	0.52	0.54	− 0.823	0.177	− 0.968	0.161
rs4652	0.39	0.4	0.42	0.43	− 0.837	0.163	− 0.987	0.101
rs4754	0.37	0.35	0.27	0.28	0.793	0.207	0.985	0.111
rs4711690	0.23	0.23	0.17	0.19	0.658	0.342	0.909	0.274
rs4789936	0.54	0.51	0.51	0.5	0.988	0.012	0.987	0.101
rs4796030	0.5	0.52	0.56	0.56	0.987	0.101	− 0.996	0.054
rs4880	0.45	0.47	0.5	0.49	− 0.887	0.113	− 0.959	0.183
rs4919510	0.17	0.22	0.19	0.2	− 0.702	0.298	− 0.972	0.151
rs4986790	0.03	0.06	0.06	0.06	− 0.985	0.015	− 0.996	0.054
rs4986791	0.03	0.06	0.06	0.06	− 0.985	0.015	− 0.996	0.054
rs5744168	0.03	0.05	0.06	0.05	− 0.915	0.085	− 0.914	0.266
rs6194	0.003	0.001	0.0001	0.0005	0.972	0.028	0.978	0.135
rs63750447	0.007	0.0006	0	0.0002	0.991	0.009	0.994	0.070
rs6413413	0.0067	0.004	0.006	0.005	0.567	0.433	0.751	0.460
rs6493	0.19	0.18	0.17	0.17	0.933	0.067	0.996	0.054
rs6494	0.2	0.21	0.22	0.2	− 0.430	0.570	− 0.414	0.728
rs6505162	0.58	0.56	0.46	0.45	0.780	0.220	1.0	0.010
rs6513497	0.1	0.11	0.07	0.06	0.565	0.435	0.987	0.101
rs698	0.24	0.24	0.39	0.37	− 0.698	0.302	− 0.976	0.140
rs699517	0.48	0.49	0.31	0.34	0.686	0.339	0.998	0.167
rs709816	0.36	0.47	0.35	0.4	− 0.309	0.691	− 0.417	0.726
rs7165402	0.12	0.16	0.13	0.14	− 0.569	0.431	− 0.910	0.272
rs731236	0.34	0.35	0.4	0.39	− 0.807	0.193	− 0.968	0.161
rs762551	0.59	0.6	0.7	0.69	− 0.750	0.250	− 0.984	0.114
rs763780	0.04	0.06	0.05	0.05	− 0.715	0.285	− 0.996	0.054
rs8113645	0.61	0.68	0.64	0.68	− 0.812	0.188	− 0.873	0.324
rs8177812	0.22	0.17	0.13	0.14	0.948	0.052	0.983	0.118
rs897986	0.69	0.68	0.64	0.61	0.711	0.289	0.888	0.304
rs910924	0.13	0.17	0.27	0.25	− 0.867	0.156	− 0.999	0.146
rs937283	0.25	0.27	0.41	0.38	− 0.743	0.257	− 0.966	0.166

1. Bold values indicate a statistically significant difference in allele frequency between Ardabil and other populations
2. * Our results
3. **Comparing our results with Iran, Europe, and World
4. *** Comparing our results with Europe and World

 

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Significant differences of allele distribution among case and control groups​

Based on their significant differences with other populations and the frequency of the variant in our population (Table 1), seventeen variants were selected for evaluation in terms of frequency difference between two case and control groups. The genotype frequencies of the variants rs12220909, rs2292832, rs2505901, rs33927012, rs4789936, rs6194, and rs63750447 did not deviate from HWE, while the others did deviate from HWE. Among the 17 selected variants, the variants rs1050631, rs12983273, rs1695, rs2274223, rs2292832, rs2505901, rs33927012, rs374569, and rs6505162 showed significant differences (Table 2).

 

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Discussion​

Somatic mutations in oncogenes and tumor suppressor genes, in collaboration with environmental exposures such as tobacco and carcinogenic chemicals, can trigger cancer. While hereditary cancers account for only 5–10% of all cases and are associated with germline alterations in oncogenes and tumor suppressor genes, non-hereditary cancer can be predisposed by single-nucleotide polymorphisms (SNPs). These genetic variants, known as “drivers,” primarily cause uncontrolled cellular proliferation and occur in “cancer driver genes” [30]. A recent study identified about 570 cancer driver genes that mediate molecular regulatory networks and changes in the tumor microenvironment. Mutations in these genes, as well as abnormal expression levels, can lead to uncontrolled tumor cell proliferation, invasion, and drug resistance [31].
Some case–control studies have shown a correlation between SNPs and susceptibility to gastric cancer in the Ardabil population. Among these, the relationship between IL-1β-511 and MTHFR C677T polymorphisms and gastric cancer is notable [32, 33]. However, some SNPs previously reported as gastric cancer-related variants were not associated with this population, including the polymorphism P53 Arg72Pro [34].
Previous studies have suggested an important role of miR-149 in carcinogenesis. This microRNA acts as a tumor suppressor gene in some cancers and an oncogene in others. Upregulation of miR-149 has been reported in AML, prostate cancer, glioblastoma, and melanoma, while it is downregulated in gastric, hepatocellular, renal cell, lung, colorectal, breast, and thyroid cancers, as well as neuroblastoma. Upregulation of miR-149 in tumor cells and gastric cancer cell lines inhibits cell proliferation and induces G0/G1 cell cycle arrest [35].
In our general population, the frequency of the C allele of rs2292832 (a T to C nucleotide change in miR-149) was found to be the lowest (0.51 vs. 0.64 for Iran, 0.7 for Europe, and 0.7 for the world), indicating a significant difference (P = 0.017). Consistent with this finding, a lower frequency of the C allele (P = 0.001) and the genotypes TC (P = 0.046), CC (P = 0.01), and TC+CC (P = 0.01) were observed compared to the controls. Based on the reported relationship between a reduced risk of gastric cancer and the rs2292832 C allele in two case–control studies on Chinese and Korean populations, as well as a meta-analysis [36,37,38], the lower frequency of the C allele in Ardabil could be associated with a higher risk of gastric cancer. However, the absence of deviation from Hardy–Weinberg equilibrium and the lack of association in other studies [39,40,41] necessitate further research, including cohort investigations, in our population.
The variant rs12983273 C>T is located in the MIR371B and MIR373 genes. It has been reported that hsa-miR-373 is downregulated in the gastric cancer recurrent group [42]. PRDM4, which has been identified as a risk biomarker for gastric cancer patients, is regulated by hsa-miR-373 [43]. In addition to the upregulation of miR373 in gastric adenocarcinoma tissue and gastric carcinoma cell lines, the inhibition of migration and invasion in some gastric cancer cell lines has been observed [44].
There were no reported associations for rs12983273 and female neoplasm, breast cancer, ESCC, Oral Premalignant Lesions (OPL), and esophageal cancer risk [45]. Compared to Iranian, European, and world populations, the T allele has a lower frequency in Ardabil (0.107 vs. 0.136). This difference tends to be significant (P = 0.017). Consistent with this finding, the frequency of allele T and genotype CT+TT in cases affected with gastric cancer were lower than in controls (P values of 0.02 and 0.031, respectively). Cohort studies are needed to validate the impact of rs12983273 in conferring gastric cancer predisposition in our population.

 

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PSCA (Prostate Stem Cell Antigen), a member of the LY-6 family of surface proteins, is abundantly expressed in the normal esophagus and stomach but undetectable in esophageal or gastric tumors. PSCA is expressed in differentiating gastric epithelial cells, and in vitro studies have detected its cell proliferation inhibition activity and silencing in gastric cancer [104].

Various SNPs in the PSCA gene have been associated with gastric cancer in Chinese, Korean, Japanese, Tibetan, and Caucasian populations [105,106,107,108,109,110]. The variant rs2976391 C>A is an intronic variant of the PSCA gene. In a meta-analysis with 81,961 cases affected by gastric cancer and 442,932 healthy controls, a strong association was found for this variant [111]. The frequency of allele A in our population was found to be greater than in other populations (0.57 vs. 0.41 in Iran, 0.4 in gnomAD, and 0.405 in 1000G). This suggests that this variant may play a role in conferring gastric cancer susceptibility in Ardabil province.
https://jmhg.springeropen.com/articles/10.1186/s43042-024-00474-w#Tab1

 

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The PLCE1 (Phospholipase C epsilon 1) gene is involved in the regulation of cell growth, differentiation, and oncogenesis. The substitution of a C nucleotide with a T at residue 4406 of the PLCE1 gene results in the substitution of threonine amino acid with isoleucine, known as rs3765524. This variant has been reported to be correlated with an increased risk of gastric cancer in some populations, including Chinese and Kashmir Valley [52, 53]. Despite finding no association in the north of Iran [62], the higher frequency of allele T in Ardabil (0.41 vs. 0.35 in Iran and 0.31 in gnomAD) may be related to the high incidence of gastric cancer.

The frequency of allele C in the DNA repair gene ERCC2 rs3810366 is higher in the Ardabil population compared to other populations (Ardabil: 0.54; Iran: 0.52; 1000G: 0.42). This finding is consistent with studies conducted on southern Chinese and Taiwanese populations (112).

The differences in observed frequencies, whether significant or not, motivate researchers to conduct cohort studies in the Ardabil population. By doing so, we aim to identify prognostic factors that can help diagnose individuals predisposed to gastric cancer in this population.

 

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Population in Adarbil is not Persian but Azerbaijan people

 

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