Genetic Variations miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G and the Risk of Recurrent Pregnancy Loss in Korean Women

This study investigated the genetic association between recurrent pregnancy loss (RPL) and microRNA (miRNA) polymorphisms in miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G in Korean women. Blood samples were collected from 381 RPL patients and 281 control participants, and genotyping of miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G was carried out by TaqMan miRNA RT-Real Time polymerase chain reaction (PCR). Four polymorphisms were identified, including miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G. MiR-10a dominant model (AA vs. AT + TT) and miR-499bGG genotypes were associated with increased RPL risk (adjusted odds ratio [AOR] = 1.520, 95% confidence interval [CI] = 1.038–2.227, p = 0.032; AOR = 2.956, 95% CI = 1.168–7.482, p = 0.022, respectively). Additionally, both miR-499 dominant (AA vs. AG + GG) and recessive (AA + AG vs. GG) models were significantly associated with increased RPL risk (AOR = 1.465, 95% CI = 1.062–2.020, p = 0.020; AOR = 2.677, 95% CI = 1.066–6.725, p = 0.036, respectively). We further propose that miR-10aA>T, miR-30cA>G, and miR-499bA>G polymorphisms effects could contribute to RPL and should be considered during RPL patient evaluation.


Introduction
Recurrent pregnancy loss (RPL) is generally defined as three or more consecutive losses of pregnancy before 20 weeks of gestation. However, the American Society for Reproductive Medicine recently redefined RPL as more than two consecutive pregnancy losses [1]. Worldwide, RPL is a serious health problem that is significantly associated with morbidity and mortality. Factors contributing to the etiology of RPL include advanced maternal age, maternal anatomic anomalies, placental anomalies, chromosomal abnormalities, endocrine dysfunction, antiphospholipid syndrome, hereditary thrombophilia, psychological trauma, and environmental factors, such as smoking, excessive alcohol consumption, and stress [2]. Additionally, women who miscarry during their first pregnancy are 5% more likely to develop RPL than healthy women [3]. Although many relevant factors have been identified, the root cause of most cases of RPL remains unknown. RPL is also associated with blood clotting angiogenesis and immune disorders. XX; and no history of miscarriage. The study abided by the Declaration of Helsinki and was approved by the Institutional Review Board of CHA Bundang Medical Center (IRB approval no. BD2010-123D), and written informed consent was obtained from all participants. All RPL patients had suffered a minimum of two consecutive spontaneous miscarriages at an average gestational stage of 7.36 ± 1.93 weeks. Pregnancy loss was diagnosed based on the results of hCG tests, ultrasound, and/or physical examination before 20 weeks of gestation. None of the participants had a history of smoking or alcohol use. The following parameters were also measured: activated partial thromboplastin time (aPTT), body mass index (BMI), blood urea nitrogen (BUN), creatinine, estradiol (E2), follicle-stimulating hormone (FSH), luteinizing hormone (LH), platelet (PLT) count, and prothrombin time (PT), using participant blood samples.
Patients with the following conditions were excluded from the study: RPL or implantation failure due to hormonal, genetic, anatomic, infectious, autoimmune, or thrombotic causes. Anatomic causes were evaluated using hysterosalpingogram, hysteroscopy, computed tomography, and magnetic resonance imaging to detect intrauterine adhesions, septate uterus, and uterine fibroids. Hormonal causes, including hyperprolactinemia, luteal insufficiency, and thyroid disease, were evaluated by blood analyses. Infectious causes, such as the presence of Ureaplasma urealyticum or Mycoplasma hominis, were evaluated by bacterial culture. Autoimmune causes, including antiphospholipid syndrome or lupus, were evaluated using lupus anticoagulant and anticardiolipin antibodies. Thrombotic causes, such as thrombophilia, were evaluated by identification of protein C and S deficiencies and by detection of β-2-glycoprotein 1 antibodies.

Chromosome Analysis
Chromosome analysis was conducted according to standard cytogenetic methods. Peripheral blood lymphocytes were cultured for 70 h, and then KaryoMAX Colcemid Solution (Gibco) was added when the chromosomes were at the metaphase stage. KCl (0.05 M) was added as a hypotonic agent, and the cells were fixed for harvest using a fixative formed by adding one volume of acetic acid to two volumes of methanol. Metaphase chromosome preparations obtained after cell culture were stained using the Giemsa-Trypsin-Giemsa (GTG) banding method.

Genotyping
Genomic DNA was extracted from anticoagulant-treated peripheral blood samples using a G-DEX Genomic DNA extraction kit (iNtRON Biotechnology, Seongnam, Korea) [28,29]. Briefly, Proteinase K was added to a microcentrifuge tube, followed by 30 µL of blood. Next, 300 µL of Lysis solution was added, and the samples were vortexed and incubated at 55 • C for 10 min. A total of 350 µL of ethanol was then added to each sample, and the samples were bound, washed, and eluted according to the manufacturer's protocol. Four miRNAs (SNPs) were selected using the NCBI human genome SNP database (dbSNP, http://www.ncbi.nlm.nih.gov/snp (accessed on 13 March 2019)). The SNPs miR-10aA>T (rs3809783), miR-30cA>G (rs113749278), miR-181aT>C (rs16927589), and miR-499bA>G (rs37464444) are either mature-form (rs3746444, rs-formnp8978) or pri-form (rs3809783, rs16927589). miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G were genotyped according to TaqMan ® SNP Genotyping Assays system (Applied Biosystems, Foster City, CA, USA). Based on the intensity of fluorescence signals of FAM and VIC, samples were automatically classified into one of three groups corresponding to the genotypes AA, AG, or TT of miR-10aA>T; AA, AG, or GG of miR-30cA>G; TT, TC, or CC of miR-181aT>C; and AA, AG, or GG of miR-499bA>G. The basic principle of the assay is as follows: when the allele-specific probe is fully hybridized to the template DNA, Taq polymerase cleaves the reporter dye, leading to fluorescence emission. However, if a single base mismatch exists between the probe and template DNA, hybridization is inefficient, and reporter dye fluorescence is thus reduced. The sequences of the SNPs were as follows: Plasma PAI-1, total cholesterol, uric acid, and homocysteine levels were measured in participant blood samples. Plasma was separated by centrifugation of whole blood at 1000× g for 15 min. PAI-1 levels were determined using a human serpin E1/PAI-1 immunoassay (R&D Systems, Minneapolis, MN, USA). Uric acid and total cholesterol levels were measured using enzymatic colorimetric tests (Roche Diagnostics, GmbH, Mannheim, Germany). Homocysteine levels were measured using a fluorescence polarization immunoassay with an Abbott IMx analyzer (Abbott Laboratories, Abbott Park, IL, USA).

Statistical Analyses
The significance of differences in the frequencies of the miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G SNPs between the control and patient groups were assessed using Fisher's exact test and a logistic regression model. p-values were calculated using two-sided t-tests for continuous variables and chi-square tests for categorical variables. Allele frequencies were calculated to investigate the deviation from Hardy-Weinberg equilibrium. The genotype distribution of RPL patients and controls with ≥h or ≥o pregnancy loss was investigated. Odds ratios (ORs), adjusted odds ratios (AORs), and 95% confidence intervals (CIs) were used to examine the associations between various miRNA polymorphisms and RPL risk. Data are presented as the mean ± SD for continuous variables or a percentage for categorical variables. The results of the allele and genotype combination analysis were consistent with those derived from Fisher's exact test during regression analysis.
Statistical analyses were carried out using MedCalc software, version 12.1.4 (MedCalc Software bvba, Mariakerke, Belgium) or GraphPad Prism 4.0 software (GraphPad Software, Inc., San Diego, CA, USA). Logistic regression analysis was applied to data regarding baseline characteristics, genotype frequencies, genotype combinations, and allele combinations for quantitative traits shown in Table 2, Table 3, Table 4 and Table 5. The HAPSTAT program (v.3.0, www.bios.unc.edu/~lin/hapstat/ (accessed on 10 April 2018)), which exhibits a strong synergistic effect, was used to estimate the frequencies of polymorphic haplotypes. A p-value < 0.05 indicated statistical significance. HAPSTAT allows testing of haplotype (or allele combination) effects by maximizing the likelihood (from the observed data) that properly accounts for phase uncertainty and study design. False-positive discovery rate (FDR) correction was used to adjust multiple comparison tests and associations with FDRadjusted p-values < 0.05 were considered statistically significant [30]. FDR calculation is also used for multiple hypotheses testing to correct for multiple comparisons. Multifactor dimensionality reduction (MDR) analysis was used to determine the best-model gene-gene interaction for RPL risk. The advantage of using MDR is that it overcomes the sample size limitations often encountered during logistic regression analysis in studies of high-level interactions. The MDR method consists of two main steps. First, the best combination of multi-factors is selected, and second, genotype combinations are classified into high-and low-risk groups [31]. We constructed all possible allelic combinations by MDR analysis to identify combinations with strong synergy. Allelic combinations for multiple loci were estimated using the expectation-maximization algorithm with SNPAlyze (v. 5.1; DYNA-COM Co, Ltd., Yokohama, Japan), and those having frequencies < 1% were excluded from statistical analysis. We also applied multiple regression models to further explain the results of the allelic combination analysis. Genetic interaction analyses were performed using the open-source MDR software package (v.2.0), which is available at www.epistasis.org (accessed on 15 March 2018).

Prediction of miRNA Binding and Luciferase Reporter Assay
An online search was conducted to identify targets for miR-10a, miR-30c, miR-181a, and miR-499b using the TargetScan (http://www.targetscan.org (accessed on 21 May 2018)) and miRIAD databases (http://bmi.ana.med.uni-muenchen.de/miriad/ (accessed on 16 May 2018)). We used these databases to predict miRNAs that target overlapping regions of PAI-1 mRNA transcripts. Target mRNA sequences, particularly within the 3 -UTR, are often obtained from the National Center for Biotechnology Information (www.ncbi.nlm.nih.gov/ (accessed on 26 September 2018)). We found that miR-30c, miR-10a, and miR-181a were predicted to be targets of the PAI-1 3 -UTR. Therefore, a luciferase reporter assay was used to evaluate the roles of miR-30c, miR-10a, and miR-181a in regulating the expression of target genes, as previously described. Briefly, wild-type pGL4.13-luciferase vector (Promega, Madison, WI, USA). constructs containing the 3 -UTRs of the PAI-1 gene were generated by amplifying the 3 -UTR region clone (OriGene, Rockville, MD, USA) and cloning the amplification products into the downstream region of the pGL4.13 vector (Promega, Madison, WI, USA) using the XbaI and FseI endonucleases (New England BioLabs, Ipswich, MA, USA). Positive clones were selected by sequence-specific PCR, restriction enzyme digestion, and DNA sequencing. Ishikawa cells were cultured in Dulbecco's modified Eagle's medium (DMEM) (Thermo Fisher Scientific, Inc. Waltham, Massachusetts, USA). All medium was supplemented with 10% fetal bovine serum (FBS) (Thermo Fisher Scientific, Inc. Waltham, Massachusetts, USA) and 1% penicillin/streptomycin (Thermo Fisher Scientific, Inc. Waltham, Massachusetts, USA). All cell lines were maintained in a CO 2 incubator (5% CO 2 ) at 37 • C. The Ishikawa cells used in this study were endometrial and are commonly used in RPL studies. Next, miR-10a, miR-30c, and miR-181a mimics (50 nM) were co-transfected into Ishikawa cells with 200 ng of the 3 -UTR of PAI-1 in pGL4.13 constructs using lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). After 16 h of incubation, the luciferase activity was measured using a dual-luciferase reporter assay system (Promega, Madison, WI, USA). Each transfection was performed as triplicates.

Baseline Characteristics of Recurrent Pregnancy Loss Patients and Control Subjects
The characteristics of RPL patients and control subjects are summarized in Table 1. The mean age was approximately 33 years for both groups, and both groups were 100% female. PLT count, aPTT, and concentrations of E2 and LH were greater in RPL patients than in controls (p = 0.0007, p = 0.005, p = 0.001, and p = 0.011, respectively). There were no significant differences in age, BMI, uric acid level, or FSH level between the two groups.  Table 2 shows the distribution of genotypes in RPL patients with ≥3 or ≥4 pregnancy losses and control subjects. Significant differences in the miR-10a SNP were observed between the RPL and control groups and were significantly correlated with RPL prevalence. Consistently, the absence of these miRNA polymorphisms showed a negative correlation with RPL. The associations of these polymorphisms were very interesting in RPL patients because the miRNA polymorphisms were related to decreased RPL, but they were not associated with RPL risk (Table 2). In addition, the number of RPL patients with risk factors was very small. Therefore, the associations with RPL occurrence will require further investigation. miR-10aA>T (chr17:48579816, rs3809783), miR-30cA>G (chr6:71377017, rs113749278), miR-181aT>C (chr9:124692981, rs16927589), and miR-499bA>G (chr20: 34990400, rs37464444) were all in the miRNA mature-form (rs3746444, rs-formnp8978) or pri-form (rs3809783, rs16927589). The SNPs in miRNA genes, including pri-miRNAs, pre-miRNAs, and mature miRNAs, could potentially influence the processing and/or target selection of miRNAs. Since we selected four SNPs in pri-form or mature-form, we wanted to determine whether all these miRNAs could influence the expression and regulation of target genes. Based on the intensity of FAM and VIC fluorescence, samples were automatically classified into one of three groups corresponding to genotypes AA, AT, or TT of miR-10aA>T; AA, AT, or GG of miR-30cA>G; TT, TC, or CC of miR-181aT>C; and AA, AG, or GG of miR-499bA>G. Abbreviations: AOR, adjusted odds ratio; CI, confidence interval; FDR-P, false-positive discovery rate-corrected; PL, pregnancy loss; RPL, recurrent pregnancy loss.

Allele Combination Analysis of miRNA Polymorphisms in Recurrent Pregnancy Loss Patients and Control Subjects
The results of allele combination analyses of miRNA polymorphisms in RPL patients and control subjects are shown in Table 5 and Supplementary Tables S2-S4

Differential Expression of the miR-10aA>T, miR-30cA>G, and miR-499bA>G Polymorphisms
The impact of SNPs on the interaction of miR-10aA>T, miR-30cA>G, miR-181aT>C, and miR-499bA>G on their targets was investigated by constructing various expression plasmids (pri-miR-10aA, pri-miR-10aG, pri-miR-30cA, pri-miR-30cG, pre-miR-181aT, pre-miR-181aG, pri-miR-499bA, and pri-miR-499bG) under control of the cytomegalovirus (CMV) promoter with either the major or minor allele. These plasmids were used in a dual luciferase assay performed with the 3 UTR of PAI-1, one of the predicted targets of miR-10a, miR-30c and miR181a, in Ishikawa human endometrial cells. A schematic diagram of a gene with a 3 -UTR of PAI-1 containing possible miR-10a and miR-30c binding sites in a conserved region is shown in Figure 1A,B. The luciferase activity of the 3 UTR of PAI-1 was significantly lower in pre-miR-10a having the A allele as compare to pre-miR-10a having the T allele (p < 0.05) ( Figure 1C). Similarly, the luciferase activity of the 3 UTR of PAI-1 was significantly lower in the pre-miR-30c with the A allele as compared to pre-miR-30c with the G allele (p < 0.05) ( Figure 1D).   (C) Dual-luciferase reporter assays were performed to test the interaction of hsa-miR-10aA>T and its targeting sequence in the PAI-1 3′-UTR using constructs containing the predicted targeting sequence (pGL4.13-PAI-1 3′-UTR) cloned into the 3′-UTR of the reporter gene. Luciferase expression levels were normalized against Renilla luciferase expression. Data represent three independent exper-iments with triplicate measurements. ** p < 0.05. (D) Dual-luciferase reporter assays were performed to test the interaction of miR-30cA>G and its target sequence in the PAI-1 3′-UTR using constructs containing the predicted targeting sequence (pGL4.13-PAI-1 3′-UTR) cloned into the 3′-UTR of the reporter gene. Luciferase expression levels were normalized against Renilla luciferase expression. Data represent three independent experiments with triplicate measurements. ** p < 0.05. Figure 1. Expression of miR-10aA>T, miR-30cA>G, and the regulation of 3 -UTR of PAI-1 by miR-10a and miR-30c. (A,B) A schematic representation of gene with 3 -UTR of PAI-1 that contain possible miR-10a and miR-30c binding sites in conserved regions. (C) Dual-luciferase reporter assays were performed to test the interaction of hsa-miR-10aA>T and its targeting sequence in the PAI-1 3 -UTR using constructs containing the predicted targeting sequence (pGL4.13-PAI-1 3 -UTR) cloned into the 3 -UTR of the reporter gene. Luciferase expression levels were normalized against Renilla luciferase expression. Data represent three independent exper-iments with triplicate measurements. ** p < 0.05. (D) Dual-luciferase reporter assays were performed to test the interaction of miR-30cA>G and its target sequence in the PAI-1 3 -UTR using constructs containing the predicted targeting sequence (pGL4.13-PAI-1 3 -UTR) cloned into the 3 -UTR of the reporter gene. Luciferase expression levels were normalized against Renilla luciferase expression. Data represent three independent experiments with triplicate measurements. ** p < 0.05.

Discussion
Increasing evidence suggests that miRNAs play critical roles in the pathophysiology of various reproductive disorders [14,15,32]. Here, we investigated whether four pre-miRNA SNPs (miR-10a, miR-30c, miR-181a, and miR-499b) were associated with the risk of RPL in a cohort of Korean women. Specifically, we focused on the genotypes and allele combination of the selected miRNA polymorphisms and aimed to determine how they affected the risk of RPL. Using a genotype-based analysis method, we found that the GG and dominant (AA vs. AG + GG) miR-499b genotypes were significantly more common in RPL patients (PL ≥ 3 and PL ≥ 4, p < 0.05) than control subjects. In allele combination analyses, the AA/GG and AG/AG genotypes of miR-30cA>G/miR-499A>G were significantly more common in RPL patients than in controls.
As the activities of many genes are interconnected in complex conditions such as RPL, gene-gene interactions may affect gene-disease associations. The MDR method enables the detection of gene-gene interactions, regardless of the chromosomal locations of the genes [33]. We used a novel genotype-based MDR approach to examine the effects of potential interactions between different miRNAs on RPL risk. These results of these analyses, which examined the effects of four miRNA polymorphisms associated with RPL, suggested that gene-gene interactions involving these four miRNA polymorphisms also play roles in determining the risk of RPL. Allele combination MDR analyses indicated that the two combination conferred by the miR-10aA>T/miR-181aT>C/miR-30cA>G/miR-499A>G (A-T-G-G and T-C-G-A), the two combination conferred by the miR-10aA>T/miR-181aT>C/miR-30cA>G (T-T-A, T-C-G), the two combination conferred by the miR-10aA>T/miR-30cA>G/miR-499A>G allele combination (C-A-G, C-G-A), and the genotype conferred by the miR-10aA>T/miR-30cA>G allele combination (T-A) occur more frequently in patients with RPL than control subjects, suggesting a significant association with increased risk of RPL (all p < 0.05). In addition, the miR-10aA>T/miR-181aT>C/miR-30cA>G allele combination T-T-G and the miR-10aA>T/miR-30cA>G/miR-499A allele combination C-G-G were found to be less frequent in RPL patients than controls, suggesting these combinations exert a protective effect (all p < 0.05).
SNPs that occur in miRNA genes, miRNA machinery genes, or miRNAs that target genes involved in miRNA synthesis or function could adversely affect downstream gene expression [34]. Several studies have provided evidence supporting the critical role of miRNAs in RPL [35]. A previous study demonstrated that miR-499 was associated with the transforming growth factor (TGF)-β signaling pathway [24]. Furthermore, the 3 -UTR of the TGF-β3 gene has been shown to contain a putative binding site for miR-30c (rs928508) (http://www.targetscan.org (accessed on 21 May 2018)), which targets the drug metabolism gene SULT1A1 [25]. Several TGF-β superfamily members perform critical functions in the female reproductive system. Specifically, these proteins regulate all processes of ovarian follicle development, including granulosa and theca cell proliferation, primordial follicle recruitment, gonadotropin receptor expression, ovulation, oocyte maturation, luteinization, and corpus luteum formation [36]. Additionally, the 3 -UTR of the prostaglandin F2 receptor inhibitor gene has been shown to contain a predicted binding target for miR-604 (http://www.targetscan.org (accessed on 21 May 2018)), and prostaglandin F2 is required for placenta retention [37]. Furthermore, the miR-10aA>T polymorphism has been associated with regulation of IL-6 expression [26], and a previous study reported abnormal IL-6 expression in both animal models and patients with recurrent spontaneous abortions [38].
An online search for miR-10a, miR-30c, miR-181a, and miR-499b targets using the Target Scan and miRIAD databases (http://bmi.ana.med.uni-muenchen.de/miriad/ (accessed on 21 May 2018)) returned many putative mRNA targets. Among these targets, we focused on PAI-1 for further functional analyses of miR-10a, miR-30c, and miR-181a because this gene has been shown to play several important roles in pregnancy and infertility [27]. PAI-1 is the primary inhibitor of plasminogen activators, including tPA and uPA. In the human placenta, PAI-1 is expressed in the extravillous interstitial and vascular trophoblasts. During implantation and placentation, PAI-1 inhibits extracellular matrix degradation, which thereby inhibits trophoblast invasion. We reviewed the literature regarding various reproductive diseases in which PAI-1 plays a role. Elevated PAI-1 levels have been detected in patients with RPL, preeclampsia, intrauterine growth restriction, gestational diabetes mellitus (GDM), endometriosis, and PCOS. Furthermore, both GDM and PCOS development have been reported to be related to the genetic role of the 4G/5G polymorphism in PAI-1. In general, elevated blood levels of PAI-1 are associated with an increased risk of infertility and poor pregnancy outcomes. In contrast, deficiency of PAI-1 results in transiently impaired placentation in mice [39], and deficiency of the PAI-1 gene is associated with abnormal bleeding after trauma or surgery in humans [40]. PAI-1 functions as a major inhibitor of fibrinolysis, and its overexpression leads to fibrin accumulation and placental insufficiency during pregnancy. PAI-1 acts as a major inhibitor of fibrinolysis, resulting in fibrin accumulation and insufficient placental formation due to overexpression. Previous reports also suggested that elevation of PAI-1 levels is the most frequent hemostasis-related abnormality associated with unexplained RPL [41]. Thus, increased expression of PAI-1 leading to inhibition of fibrinolysis is believed to be the main cause of RPL.
To determine whether polymorphisms in miR-10a, miR-30c, and miR-181a affect target gene expression, we compared the expression levels of the 3 -UTR of PAI-1 harboring the different polymorphisms of miRNAs in Ishikawa human endometrial cells. Aberrant PAI-1 expression resulting from the expression of miR-10a with the A allele was significantly lower (p < 0.05) than aberrant PAI-1 expression resulting from the expression of miR-10a with the T allele. In addition, the expression of miR-30c with the A allele was significantly lower (p < 0.05) than expression of premature and mature miR-30c with the G allele.
Expression of genotypes of miR-30cG as well as those of miR-10aT led to reduced expression of PAI-1 mRNA. These results suggest that SNPs in miR-30c and miR-10a regulate the expression of the PAI-1 gene. PAI-1-mediated inhibition of fibrinolysis and fibrin accumulation is currently believed to be the principal culprits for RPL; however, further studies are required to fully elucidate the underlying mechanisms.
FSH is the primary gonadotropin responsible for regulating the progression of pregnancy [42]. Optimal levels of FSH, especially during the first few months of pregnancy, are critical for proper formation of the placenta [43]. Our clinical data indicated significant changes in FSH levels in RPL patients harboring the miR-30cA>G polymorphism. We, therefore, hypothesized that abnormal regulation of PAI-1 expression mediated by mutant miR-30c SNP results in aberrant FSH expression or disruption of the normal response to FSH. Imbalances in homocysteine and folate levels in particular are thought to contribute to low birth weight [44]. Specifically, higher homocysteine and lower folate concentrations during early pregnancy have been reported to be associated with lower placental weight and birth weight. However, we did not observe any associations between folate and homocysteine concentrations and placental weight.
We found that the dominant miR-499b AG genotype (AA vs. AG + GG) was significantly more frequent in RPL patients (p < 0.05). Earlier studies used a global approach to identify and profile miRNA expression at important stages during the estrous cycle and found a role of miRNAs in ovulation. Additionally, one-way ANOVA analysis of variance of data from RPL patients ( Table 6) revealed that in comparison with miR-30cAA, the miR-30cGG genotype was associated with significantly lower aPTT, E2 (pg/mL), Hct, and T. chol (mg/dL) and significantly higher creatinine (mg/dL) and FSH (mIU/mL). Compared with miR-181aTT, the miR-181aCC genotype was associated with significantly higher homocysteine levels, suggesting this genotype is associated with increased risk of RPL (p < 0.05). Compared with miR-181aTT, the miR-181aTC genotype was associated with significantly higher T. chol levels, suggesting this genotype is associated with increased risk of RPL (p < 0.05). However, in the case of creatinine levels, the miR-181aTC genotype was associated with significantly lower levels than the miR-181aTT genotype, indicating a protective effect, although the results were inconsistent with OR and therefore, the difference was not significant.

Conclusions
We investigated the relationship between various miRNA polymorphisms and the occurrence and risk of RPL. Several genotypes and allele combinations were positively correlated with RPL occurrence and unfavorable prognoses according to reproductive disease risk factors, including FSH, LH, and E2 levels. However, this study has several limitations. First, how the miRNA polymorphisms in the PAI-1 gene affect the development of RPL remains unclear. In addition to studies of PAI-1, future follow-up studies of other RPL-related genes and the miR-10a and miR-30c targets are planned, particularly studies of the role of genes related to the TGF-β signaling pathway. As TGF-β regulates cell proliferation, apoptosis, and homeostasis, it plays a critical role in regulating the progression of pregnancy. Second, the control subjects in our study were not completely healthy because some of them had sought medical attention for other issues. Our experience shows that recruiting healthy participants through imaging and laboratory testing results in significantly reduced enrollment rates. However, enrollment of participants without imaging and laboratory testing can introduce another challenge to risk factor assessment. Lastly, the study population was restricted to Korean patients. Although the results of our study provide the first evidence suggesting that miRNA polymorphisms in the PAI-1 gene may serve as diagnostic and prognostic biomarkers for RPL, a prospective study involving a larger cohort of patients is warranted to validate these findings. A genome-wide analysis (using transcriptome-seq and miRNA-seq) is needed to identify the primary target genes, particularly the common genes regulated by these miRNAs. Determining the expression of these genes in the relevant gene-miRNA networks would provide stronger evidence in support of the results of the present research.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/biomedicines10102395/s1, Table S1: Genotype frequencies of miRNA gene polymorphisms in control subjects and recurrent pregnancy loss patients; Table S2: Four allele combination analysis of miRNA polymorphisms in recurrent pregnancy loss patients and control subjects; Table S3. Three allele combination analysis of miRNA polymorphisms in recurrent pregnancy loss patients and control subjects; Table S4. Two allele combination analysis of miRNA polymorphisms in recurrent pregnancy loss patients and control subjects.

Institutional Review Board Statement:
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of CHA Bundang Medical Center (IRB approval no. BD2010-123D).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Data Availability Statement:
The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest:
The authors declare no competing financial interests.