The association of AGO1 (rs595961G>A, rs636832A>G) and AGO2 (rs11996715C>A, rs2292779C>G, rs4961280C>A) polymorphisms and risk of recurrent implantation failure

Abstract Recurrent implantation failure (RIF) is a common reproductive clinical condition treated by fertility specialists at in vitro fertilization (IVF) clinics. Several factors affect embryo implantation including the age of the female, the quality of embryos and the sperm, genetics, immunologic factors. Here, we investigated the association of Argonaute 1 (AGO1) and Argonaute 2 (AGO2) polymorphisms and RIF. We collected blood samples from 167 patients with RIF and 211 controls. Genetic polymorphisms were detected by polymerase chain reaction (PCR) – restriction fragment length polymorphism analysis and real-time PCR. We found that the AGO2 rs4961280C>A polymorphism (adjusted odds ratio [AOR] = 1.984; P = 0.023) was significantly associated with RIF. Furthermore, in RIF patients with three or more consecutive implantation failure, the AGO2 rs4961280C>A CA genotype (AOR = 2.133; P = 0.013) and dominant model (AOR = 2.272; P = 0.006) were both significantly associated with prevalence of RIF. An analysis of variance revealed that patients with the AGO2 rs2292779C>G genotypes (CC: 6.52 ± 2.55; CG: 7.46 ± 3.02; GG: 8.42 ± 2.74; P = 0.044) and the dominant model (CC: 6.52 ± 2.55; CG+GG: 7.70 ± 2.97; P = 0.029) exhibited significantly increased white blood cell levels. Furthermore, patients with the AGO1 rs595961G>A dominant model (GG: 36.81 ± 8.69; GA+AA: 31.58 ± 9.17; P = 0.006) and the AGO2 rs4961280C>A recessive model (CC+CA: 35.42 ± 8.77; AA: 22.00 ± 4.24; P = 0.035) exhibited a significantly decreased number of CD4+ helper T cells. Our study showed that AGO1 and AGO2 polymorphisms are associated with the prevalence of RIF. Hence, the results suggest that variations in AGO1 and AGO2 genotypes may be useful clinical biomarkers for the development and prognosis of RIF.


Introduction
progression, proliferation, and differentiation that occur in the endometrium during the Genotyping 127 DNA samples were extracted from blood samples collected from the RIF patients and 128 controls using a G-DEX(TM) Genomic DNA Extraction Kit for blood (iNtRON 129 Biotechnology, Seongnam, South Korea). The classification of alleles of the genetic 130 polymorphism was confirmed to the East Asian population on the 1000Genomes study.

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Most of the genetic polymorphisms (AGO1 rs595961G>A, AGO1 rs636832G>A, AGO2 132 rs22927779C>G, AGO2 rs4961280C>A) were detected by polymerase chain reaction-133 restriction fragment length polymorphism (PCR-RFLP) and one of the genetic 134 polymorphisms (AGO2 rs11996715C>A) was detected by real-time PCR [39,40]. AGO1 rs595961G>A, AGO1 rs636832G>A, AGO2 rs2292779C>G, and AGO2 rs4961280C>A were 136 confirmed by digestion with the restriction enzymes (New England Bio Laboratories,Ipswich,137 MA, USA) at 37°C for 16 hours. The detailed information of PCR primers, restriction 138 enzymes, and size of fragments after enzymatic cleavage was showed Supplementary Table 1. 139 Furthermore, each genotype was confirmed by electrophoretic separation on 4% agarose gels. 140 For each Argonaute polymorphism, 30% of the PCR products were randomly chosen for a 141 duplicate PCR assay and confirmed by DNA sequencing to validate the RFLP findings. DNA 142 sequencing was performed using an ABI 3730xl DNA Analyzer (Applied Biosystems,Foster 143 City, CA, USA) and the concurrence of the quality of each sample was 100%.

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Statistical analysis 146 Differences in the genotype frequencies of the polymorphisms were compared between the 147 RIF patients and control subjects using a Fisher's exact test and logistic regression. The odds 148 ratio (OR) and 95% confidence interval (CI) were used as a measure of the strength of the 149 association between the genotype frequencies and RIF. The subtype analyses of RIF were 150 performed between stratified groups from implantation failure number. The OR and 95% CI 151 were also used to assess the relationship between each specific polymorphism and allele 152 combination. The associations between the polymorphisms and RIF incidence were 153 calculated using adjusted ORs (AORs) and 95% CIs from logistic regression adjusted for age. 154 Differences resulting in a P <0.05 were considered statistically significant. A false discovery

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The baseline characteristics 167 The demographic characteristics and clinical variables of RIF patients and control subjects 168 are shown in Table 1. The mean ages of the RIF patients and control subjects were 34.67 ±  Genotype frequencies of the AGO1 and AGO2 gene polymorphisms between RIF 176 patients and controls 177 We investigated the AGO1 rs595961G>A, AGO1 rs636832A>G, AGO2 rs11996715C>A, 178 AGO2 rs2292779C>G, and AGO2 rs4961280C>A polymorphisms between RIF patients including the numbers of times of RIF (RIF ≥2 and RIF ≥3) and control groups (Table 2). We 180 calculated the AOR using logistic regression analyses with respect to age. The AGO1 and 181 AGO2 polymorphism frequencies were all in Hardy-Weinberg equilibrium (P>0.05).
182 Furthermore, we detected several different associations between RIF patients and controls in 183 the genotype frequency analysis. The AGO2 rs4961280C>A CA genotype and the dominant 184 model (CC vs. CA+AA) were significantly associated with increased RIF prevalence (Table   185 2). Furthermore, in analysis of numbers of RIF, we detected associations between AGO2 186 polymorphisms and number of RIF occurrences. Specifically, RIF ≥3 was significantly 187 associated with the AGO2 rs4961280C>A polymorphism (Table 2). Next, we analyzed the allele combinations and compared the RIF patients and controls (Table   192 3). Based on the MDR method, the G-A-C-A allele combination in the AGO1 rs595961G>A,   Table 2). The results revealed that the GG/CA genotype combinations in the 213 AGO1 rs595961G>A and AGO2 rs4961280C>A polymorphisms, the CC/CA genotype 214 combinations in the AGO2 rs11996715C>A and AGO2 rs4961280C>A polymorphisms, and 215 the CA/CA genotype combinations in the AGO2 rs11996715C>A and AGO2 rs4961280C>A 216 polymorphisms were significantly associated with the increased prevalence of RIF (P<0.05).

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In addition, the CC/CA genotype combinations in the AGO2 rs2292779C>G and AGO2 218 rs4961280C>A polymorphisms was associated with increased RIF prevalence. Conversely, 219 the GG/AG genotype combinations in the AGO1 rs595961G>A and AGO1 rs636832A>G 220 polymorphisms was associated with decreased RIF prevalence.  Table 4, Figure 1A). The AGO1 rs636832A>G dominant model (AA vs.

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GG) and the dominant model (CC vs. CG+GG) were significantly associated with increased 230 white blood cell levels (Supplementary Table 3, Figure 1B). Furthermore, we found that The 231 AGO1 rs636832A>G dominant model (AA vs. AG+GG) was associated with decreased LH 232 levels (Supplementary Table 3 Table 3).

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In this study, we sought to determine novel markers with potential application in clinical 244 diagnostics. To this end, we investigated the association between five polymorphisms (AGO1 245 rs595961G>A, AGO1 rs636832A>G, AGO2 rs11996715C>A, AGO2 rs2292779C>G, and 246 AGO2 rs4961280C>A) and the occurrence of RIF in a Korean population.
Previous studies identified an association between AGO1 and AGO2 and ovarian 248 carcinoma [41], myeloma angiogenesis [42], as well as with an angiogenesis defect model 249 related to inflammation [43]. Furthermore, Argonaute 1 was associated with an angiogenic 250 pathway involving hypoxia-responsive miRNAs that could be a potentially suitable target for 251 anti-or proangiogenesis [44]. Importantly, the regulation of Argonaute 2 is reportedly the 252 safety mechanism that limits the range of the anti-inflammatory activity of miR-146a [45].

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Our previous study also demonstrated an association between miR-146a and risk of RIF [46].

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In addition, Argonaute 2 was identified as the catalytic core of mammalian RISC involved in 255 miRNA expression, and is reportedly essential to mammalian gastrulation and mesoderm 256 formation [47][48][49][50]. Consequently, AGO1 and AGO2 have previously been linked to the 257 association with implantation due to the reported association between Argonaute and secreted 258 miRNA in the human blastocyst, as well as human trophoblast [16,51].

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In accord with our hypothesis, our analyses revealed that the AGO2 rs4961280C>A 260 genotypes were significantly associated with prevalence of RIF. Notably, several factors 261 associated with RIF including white blood cell counts, FSH and LH levels, and blood urea 262 nitrogen concentrations as well as inflammation-related factors such as CD3 + pan T cells,

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CD4 + helper T cells, and CD8 + suppressor T cells have been shown to be significantly 264 associated with AGO1 and AGO2 gene polymorphisms in RIF patients. In our study, we  Table 4 [ [52][53][54][55][56][57][58]. Taken together, the results of this study provide 274 evidence that the AGO1 and AGO2 polymorphisms may play a role in RIF.

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There were several limitations to the current study that should be considered when analyses. Therefore, future studies are needed to confirm that AGO1 and AGO2 play a critical 281 role in RIF pathogenesis and to provide additional evidence that the regulation of AGO1 and 282 AGO2 expression or activation can be used as a tool to prevent RIF. Nonetheless, our 283 findings suggest that these polymorphisms may be potential biomarkers to diagnose and 284 assess risk of RIF.

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In conclusion, we identified associations between the AGO2 rs4961280C>A 286 polymorphism and prevalence of RIF in the Korean population, as well as a significant 287 association between AGO1 and AGO2 gene polymorphisms and risk factors of RIF. However, 288 the specific mechanisms underlying these effects require further investigation.