Association of microRNA gene polymorphisms with recurrent spontaneous abortion: An updated meta‑analysis
- Authors:
- Published online on: March 10, 2023 https://doi.org/10.3892/etm.2023.11878
- Article Number: 179
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Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Recurrent spontaneous abortion (RSA) or recurrent pregnancy loss (RPL) are common and significant pregnancy issue occurring in ~1-3% of couples trying to conceive. It is defined as at least two consecutive spontaneous abortions before the 20th week of pregnancy (1) Although several etiologic factors, such as uterine abnormalities, infectious or immune factors, endocrine and metabolic disorders, genetic abnormalities, acquired and inherited thrombophilia and chemical factors, are considered risk factors for RSA (2), the etiology of 40-55% of pregnant women suffering RSA remains to be elucidated (3), namely unexplained recurrent spontaneous abortion (URSA). Therefore, it is urgent to identify risk factors for the prevention and treatment of RSA. An increasing number of studies have focused on genetic factors, especially single nucleotide polymorphisms (SNPs) (4).
MicroRNAs (miRNAs) are a class of noncoding RNAs that regulate gene expression at the post-tanscriptional level by suppressing the translation of protein-coding genes by targeting mRNA 3'UTR and are involved in a wide range of life processes, including proliferation, development, differentiation, immune response and hormone secretion (5). miRNAs are estimated to regulate ~60% of human mRNA (6). According to studies (7-9), abnormal miRNA expression is implicated in the pathogenesis of RSA. Sequence variants in miRNA genes may contribute to their dysregulation. The presence of an SNP or mutation in an miRNA gene may alter the binding affinity of the miRNA to its mRNA targets, the transcription of miRNA primary transcripts and the process of the pre-miRNA into its mature, epigenetic regulation of miRNA genes (10-12). SNPs in the miRNA gene region may affect the properties and function of miRNAs, consequently contributing to RSA susceptibility by altering miRNA expression or maturation (13).
A number of studies have been conducted to investigate the association between miRNA SNPs and RSA risk, including well-known SNPs in pre-miRNA sequences such as miR-146a C/G (rs2910164), miR-196a2 T/C (rs11614913), miR-499 A/G (rs3746444) and other SNPs (14-30), but the results are not conclusive and consistent. Srivastava et al (31) first reported a meta-analysis of miRNA SNPs and RSA. The results showed that miR-196a-2 rs11614913, miR-499 rs3746444 and miR-149 rs2292832 could reduce the risk of RSA under certain genetic models. The present study performed a meta-analysis of 18 case-control studies to assess the association between miRNA SNPs and RSA susceptibility and improve understanding of the association between these polymorphisms and RSA risk.
Materials and methods
The present systematic review and meta-analysis design was prospectively based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (http://www.prisma-statement.org/PRISMAStatement/PISMAStatement.aspx). The study has been registered on PROSPERO (https://www.crd.york.ac.uk/prospero/) (ID, CRD42021230598).
Literature search strategy
The authors Xueqin Wang and Yan Xing systematically searched the online databases, including PubMed (MEDLINE, https://pubmed.ncbi.nlm.nih.gov/), EMBASE (https://www.embase.com/), Web of Science (http://www.webofscience.com/) and Cochrane Library (https://www.cochranelibrary.com/), without language limitations up till July 2022. The following keywords were used: ‘miRNA’ AND (‘recurrent pregnancy loss or RPL’ OR ‘recurrent spontaneous abortion or RSA’ OR ‘recurrent miscarriage’) AND (‘polymorphism’ OR ‘single nucleotide polymorphism’). In addition, the reference lists from the identified articles were searched manually.
Inclusion and exclusion criteria
The present meta-analysis comprised case-control studies that met the following criteria: i) The study assessed the association between microRNA gene polymorphisms and the risk of recurrent spontaneous abortion, ii) RSA was defined as at least two consecutive spontaneous abortions before the 20th week of pregnancy, iii) in all evaluated studies, a patient group (women with RSA) compared with a control group (healthy women), iv) the distribution of genotypes or alleles in both cases and controls was extracted for calculating the odds ratios (ORs) and 95% confidence intervals (CIs), v) for repeated studies, only the studies with more complete data and longer study periods were included, vi) the selected SNPs with two or more published studies were included in the current study. Studies were excluded if i) they were letters, editorials, abstracts, reviews, case reports and studies performed on animals, ii) they did not quantify the information to calculate OR and 95% CI, iii) they were copies of previous publications, or iv) they did not meet the criteria for RSA.
Data extraction
The data from eligible studies were extracted independently by two of the authors (Xueqin Wang and Yan Xing) based on the following inclusion and exclusion criteria: First author name, year of publication, study country, ethnicity, diagnostic criteria for RSA, numbers of cases and controls, genotyping technology and polymorphisms studied. Differences were resolved by a third author (Jing Gao).
Quality assessment of included studies
Study quality assessment was independently performed by two authors (Xueqin Wang and Yan Xing) according to the Newcastle-Ottawa Scale (NOS) (32). The NOS determined the research quality based on three parameters: Study object selection, group comparability and exposure factor measurement. The NOS employs a star grading system that ranges from zero stars (worst) to nine stars (best). In brief, each study received a maximum of nine points: Four for selection, two for comparability and three for outcomes. Studies with a score of ≥6 points were considered high quality.
Statistical analysis
In the present study, ORs and 95% CIs were used to assess the association between microRNA gene polymorphisms and RSA risk. The pooled ORs and 95% CIs were calculated and their significance was determined by P-values to clarify the potential relationships. P<0.05 was considered to indicate a statistically significant difference. The present study analyzed five genetic patterns of each microRNA (allele pattern, homozygous model, heterozygous model, recessive model and dominant model) (33). Heterogeneity was measured using the chi-square test-based Q-test and I2 statistics. If significant heterogeneity existed (significant heterogeneity, P<0.10 and I2>50%), the random-effects model was used and if not (no heterogeneity, P>0.10 and I2<50%), the fixed effect model was used. The present study conducted a sensitivity analysis to evaluate the effect of each study on the combined OR by sequentially excluding individual studies to investigate the potential sources of heterogeneity and verify the reliability of the meta-analysis. As the number of included studies in each SNP was <10, publication bias evaluation was not performed.
Results
Characteristics of eligible studies
The PRISMA flow chart of the literature search and selection process is detailed in Fig. 1. A total of 41 articles were collected from the databases through a literature search using different combinations of key terms. After removing the duplicate literature and meta-analysis, 37 studies were evaluated for eligibility. A total of 13 studies were excluded (eight were not about miRNA polymorphisms, three were about recurrent implantation failure, one was a missing genotype in miRNA SNPs and one was about spontaneously aborted fetuses). Therefore, 24 studies were considered eligible for the current meta-analysis (13-30,34-39). A total of five studies were excluded because the selected SNPs in these studies were reported in only one study (34-38). Finally, the quality of 19 studies (13-30) was assessed using the NOS and all studies scored ≥6 stars or more, indicating high quality.
Table I summarized study characteristics of the 19 included studies. There were a total of 3,850 cases and 4,312 controls involving 10 SNPs of microRNAs: miR-196a-2 rs11614913 (seven studies), miR-449 rs3746444 (five studies), miR-146 rs2910164 (four studies), miR-125a rs12976445 (four studies), miR-149 rs2292832 (four studies), miR-27a rs895819 (four studies), miR-423 rs6505162 (two studies), miR-125a rs41275794 (three studies), miR-10a rs3809783 (two studies) and miR-323b rs56103835 (two studies). The distributions of microRNA gene polymorphism alleles and genotypes are shown in Table II.
Quantitative synthesis
The present meta-analysis included 10 SNPs discovered in miRNA gene loci. Table III summarizes the ORs with corresponding 95% CIs for the association between those SNPs and the risk for RSA base on different genetic models. After all included studies were pooled into the meta-analysis of each selected SNP, it was discovered that miR-149 rs2292832, miR-499a rs3746444, miR-125a rs12976445, miR-10a rs3809783, miR-125a rs41275794 and miR-323b rs56103835 SNPs were significantly associated with RSA risk (Table III). Forest plots were constructed from the findings of all included studies to show the relationship between miRNA SNPs and RSA risk under a homogeneous model (Fig. 2). Statistical heterogeneity was found in nine SNPs. A total of seven SNPs underwent subgroup analysis to detect the source of heterogeneity, while miR-423 rs6505162 and miR-125a rs41275794 were not subjected to subgroup analysis because the number of included studies was too small (n=2).
miR-196a2 rs11614913
The present study examined seven relevant papers to determine the possible association between miR196a2 rs11614913 and RSA risk. When all the eligible studies were pooled into the analysis under various models, no significant risk associations were observed, indicating they were not genetic-related risk factors for RSA risk (Table III; Fig. 2A). Additionally, substantial heterogeneity was observed. The meta-analysis did not show any correlation when subgroup analyses were performed between ethnic backgrounds.
miR-499a rs3746444
A total of five studies related to rs3746444 were included in the meta-analysis. The allele contrast and heterogeneity model showed protective ORs with significant P-values (G vs. A: OR=0.66; 95% CI=0.51-0.86; Pheterogeneity=0.03, P=0.002; AG vs. AA: OR=0.73; 95% CI=0.59-0.90; Pheterogeneity=0.15; P=0.003) (Fig. 2B; Table III). There was significantly increased association between miR499a rs3746444 A>G and RSA risk susceptibility in the recessive, dominant and homogeneous model (GG vs. GA + AA: OR=1.99; 95% CI=1.41-2.80; Pheterogeneity=0.59; P<0.0001; GG + GA vs. AA: OR=1.54; 95% CI=1.12-2.12; Pheterogeneity=0.06; P=0.007; GG vs. AA: OR=2.26; 95% CI=1.53-3.36; Pheterogeneity=0.38; P<0.00001) (Table III). The findings of subgroup analysis results demonstrated that this SNP contributed to RSA susceptibility in Asian (Korean and Indian) populations under all models (Table IV).
 | Table IVSummary of overall results and subgroup for the association between the microRNAs genes polymorphisms and RSA. |
miR-146 rs2910164
The present analysis included four studies on the miR-146a SNP. There was no significant association in any genetic model between the miR-146a rs2910164 C>G polymorphism and RSA risk (Fig. 2C; Table III). The meta-analysis did not find any correlation when subgroup analyses among ethnic backgrounds were performed (Table IV).
miR-125a rs12976445
There were four articles related to miR-125a rs12976445 C>T and URSA. Under a homogeneous model, the TT allele had a protective OR (TT vs. CC: OR=0.51; 95% CI: 0.31-0.84; P=0.008). There was no heterogeneity in the recessive model (TT vs. TC + CC: I2=0.00%; Pheterogeneity=0.65) or homogeneous model (TT vs. CC: I2=0.00%; Pheterogeneity=0.48). Significant heterogeneity was found in allele contrast (T vs. C: I2=0.85%; P=0.001), dominant model (TT + TC vs. CC: I2=0.87%; P<0.001) and heterogeneity model (TT vs. TC + CC: I2=0.87%; P<0.0001) (Fig. 2D, Table III). Subgroup analysis revealed that ethnic Chinese had an elevated risk in allelic contrast, dominant model and heterozygous model (Table IV).
miR-149 rs2292832
A total of four articles associated with miR-149 rs2292832 T>C and URSA were included. The results showed risk ORs for C allele, CC+TC and TC in allele contrast, dominant model and heterogeneity model respectively (C vs. T: OR=1.21; 95% CI=1.03-1.42; P=0.02; CC + TC vs. TT: OR=1.28; 95% CI=1.05-1.56; P=0.01; TC vs. TT: OR=1.24; 95% CI=0.73-2.12; P=0.43; Fig. 2E, Table III). Except for the heterogeneity model (TC vs. TT: I2=0.72%; Pheterogeneity=0.002), no heterogeneity was observed in any of the models. Subgroup analysis showed no significant association among different ethnic backgrounds under any models (Table IV).
miR-27a rs895819
A total of four eligible studies were included in the analysis. There was no significant connection between the miR-27a rs895819 A>G polymorphism and RSA risk in any genetic model (Fig. 2F; Table III). All of the models showed significant heterogeneity. However, subgroup analysis revealed an increased risk under allelic contrast, recessive model homozygote model and heterozygous model in the Caucasian population (G vs. A: OR=2.35; 95% CI=1.56-3.56; P<0.001; GG vs. AG + AA: OR=2.93; 95% CI=1.45-5.94; P=0.003; GG vs. AA: OR=3.63; 95% CI=1.70-7.77; P=0.009; AG vs. AA: OR=1.54; 95% CI=1.07-2.22; P=0.02; Table IV).
miR-423 rs6505162
The analysis included three eligible studies. No significant association was found between miR-423 rs6505162 C>A polymorphism and RSA risk in any genetic model (Fig. 2G, Table III). Significant heterogeneity was found in all models.
miR-125a rs41275794
For overall studies, there was a significant association of rs41275794 and RSA susceptibility in allele contrast (A vs. G: OR=2.07; 95% CI=1.47-2.92; P<0.0001), dominant model (AA + GA vs. GG: OR=2.68; 95% CI=1.59-4.52; P=0.0002), homogeneous model (AA vs. GG: OR=2.61; 95% CI=1.39-4.90; P=0.003) and heterogeneity model (GA vs. GG: OR=2.68; 95% CI=1.59-4.51; P=0.0002; Fig. 2H; Table III). Significant heterogeneity was found in the allele contrast, dominant model and heterogeneity model. Considering heterogeneity in the above gene model, a subgroup analysis by ethnicity was performed. The results showed significant and increased risk in the Chinese population under the allelic contrast, recessive, dominant, homozygote and heterozygous model. Significantly, there was increased risk for non-Chinese under the allelic contrast, dominant model and heterozygous model (Table IV).
miR-10a rs3809783
A significant association with increased risk was observed in the allele contrast (T vs. A: OR=2.12; 95% CI=1.58-2.85; P<0.00001), dominant model (TT+AT vs. AA: OR=2.68; 95% CI=1.90-3.77; P<0.00001) and heterogeneity model (AT vs. AA: OR=2.67; 95% CI=1.89-3.77; P<0.00001; Fig. 2I, Table III) when two studies were pooled into meta-analysis. No heterogeneity was found in the meta-analysis process except that the P-value and I2 in test of heterogeneity was not estimable.
miR-323b rs56103835
A significant association with increased risk was observed in the allele contrast (C vs. T: OR=1.28; 95% CI=1.01-1.63; P=0.04) with no heterogeneity (I2=30%; Pheterogeneity = 0.23) as shown in Fig. 2J and Table III, when two studies were pooled into meta-analysis.
Sensitivity analysis
Sensitivity analysis was used to examine the impact of each study on the overall OR by excluding one study at a time. The sensitivity analysis results suggested that overall effects were not influenced by any specific study, ensuring the credibility and reliability of the results of the present study (data not shown).
Discussion
RSA is a common pregnancy complication affecting 1-3% of couples trying to conceive. Studies have shown that miRNAs may play an important role in URSA and SNPs located both in the pre-miRNAs or within miRNA-binding sites are likely to influence the expression and function of the miRNA target and thus may contribute to susceptibility to URSA (28-30). The most common and widely studied SNPs in miRNAs are miR-146a rs2910164, miR-196a2 rs11614913 and miR499a rs3746444. Several studies have been conducted to investigate the relationship between these SNPs and the risks of RSA (14-30). However, the results are contradictory and inconclusive. Srivastava et al (31) performed the first meta-analysis on miRNA SNPs in RSA, suggesting that rs11614913, rs3746444 and rs2292832 biomarkers may decrease the risk of RSA under different genetic models. However, the most recent study of the above meta-analysis was published in June 2021(31). The present study conducted an independent meta-analysis on all available studies to assess the RSA risk with miRNA SNPs as well as subgroup analyses by ethnicity with larger sample size to improve understanding of the association between these polymorphisms and RSA risk. This meta-analysis reviewed the case-control literature on the association between miRNA polymorphisms and RSA risk and conducted an independent meta-analysis of eligible studies. It included 18 studies involving 3,850 cases and 4,312 controls involving 20 SNPs. miR499a rs3746444, miR-149 rs2292832, miR-125a rs41275794 and miR-10a rs3809783 may enhance the risk of RSA under different genetic models. Although there was no association between the miR-125a rs12976445 and miRNA-27a rs895819 polymorphisms and RSA, they were found to be statistically significant in certain ethnic groups of populations.
miR-196a and RSA
Preliminary data suggested a significant association of miR-196a with RSA. However, the results of the present study showed no significant association. These results were consistent with the study by Alipour et al (14), Babakhanzadeh et al (16) and Fazli et al (17). The results of the present study contradicted the findings of the meta-analysis conducted by Srivastava et al (31), which suggested that miR-196a2 T>C polymorphism may be responsible for recurrent spontaneous abortion. Significantly, some errors existed when genotypic frequencies were abstracted by Srivastava et al (31). For example, the CC and TT genotypic frequencies in the case and control groups from studies of Amin-Beidokhti et al (15) and Wang et al (30) were reversed. This could explain the differences in the current results.
miR-499a rs3746444 and RSA
Human SRY-box containing gene 6 (SOX6) can recruit c-terminal binding protein 2 (CtBP2) to repress transcription of fibroblast growth factor-3 (FGF-3), which is involved in cell proliferation and differentiation during developing embryonic tissues and SOX6 was identified as a direct target of miR-499 (40,41). It is hypothesized that miR-499 expression deregulation and dysfunctions caused by gene mutations can affect female reproduction and fertility. Studies conducted by Alipour et al (14), Fazli et al (17) and Parveen et al (23) found a significant association of miR-499a with patients with RSA, which is consistent with the conclusion of the present study. Other trials yielded inconsistent results with no significant correlation with RSA (15,19).
miR-146 rs2910164 and RSA
Alipour et al (14) suggested a positive association between miR-146a C>G polymorphism and RSA. This result is inconsistent with previous studies (16,19,23) and the present study. Studies have shown that miR-146C>G polymorphism enhances the expression of mature miR146a which suppresses breast cancer metastasis (42,43). It has also been reported that miR-146a significantly alters mRNA levels of Fas by targeting its 3'-UTR of this gene (44). Women with idiopathic infertility and recurrent pregnancy loss have lower expression of FAS, which induces apoptosis in oocytes during folliculogenesis (45).
miR-125a rs12976445 and RSA
Except for the homogeneous model, no significant association was observed in the present study in any genetic model. No significant association was observed in studies by Srivastava et al (31) in any genetic model; in their study, the genotype frequencies from pri-miR-125a rs12976445 were reversed between case and control group studies by Hu et al in 2014(18). This can somewhat explain the inconsistency with the results of the present study.
miR-149 rs2292832 and RSA
The present study observed statistical evidence for a significant association of SNP rs2292832 within the miR-149 gene with RSA under three genetic models, which indicated that the C allele and CC genotype are risk factors for RSA. This result is inconsistent with previous studies (14,31). The target genes of miR-149 are Akt1 and E2F1, which are involved in promoting cell growth and cell cycle progression (46).
miR-27a rs895819 and RSA
miR-27a rs895819 is significantly associated with increased frequency of RSA risk and repeated implantation failure (33). However, the findings of the present study did not show any association, consistent with the results of Rah et al (24) and Srivastava et al (31). The subgroup study showed no association in the Asian group but a significant association in the Caucasian group.
miR-423 rs6505162 and RSA
A study by Wang et al (29) found that SNP rs6505162C>A in coding region of miR-423 was associated with an increased risk of human URSA in 316 RSA cases and 309 controls, while Rah et al (24) and Srivastava et al (31) observed no significant correlation with RSA, which is consistent with results of the present study. Studies by Srivastava et al (31), which included the same two studies, reached the same conclusion.
miR-125a rs41275794 and RSA
Hu et al (18) identified that two functional SNP sites in pri-miR-125a affected the expression of LIFR and ERBB2 and thus increased the RSA risk. Vahedi et al (26) also reported that the number of alleles in pre-miR-125a was significantly different and the dominant inheritance model was proposed. Except for the recessive model, the present study showed that miR-125a rs41275794 significantly increases the risk of RSA in all models. Subgroup analysis also indicated that miR-125a rs41275794 may increase susceptibility to RSA. Srivastava et al (31) found no significant connection in any genetic model other than the homogeneous model. In that study, the genotype frequencies from pri-miR-125a rs41275794 were reversed between case and control group studies by Hu et al (18) in 2014. This can explain the inconsistency with the results of the present study.
miR-10a rs3809783 and RSA
Studies by Li et al (21) and Vahedi et al (26) discovered that miR-10a rs3809783 A>T is conducive to a genetic predisposition to RSA, which is consistent with the current findings. miR-10a rs3809783 A>T disrupts the production of mature miR-10a and reinforces the expression of Bim (21).
miR-323b rs56103835 and RSA
Studies by Wang et al (28) discovered that miR-323b rs56103835 T>C was associated with an increased risk of human URSA, while Vahedi et al (26) found no significant association with RSA. No significant association was observed in any genetic model except the allele contrast in the present study.
The present meta-analysis has the advantages of including more literature, studying more gene sites and conducting more in-depth subgroup analysis than the previous meta-analysis (31). However, in addition to the significant heterogeneity, a limitation of the present meta-analysis was that the number of eligible studies included in the total is insufficient to obtain a precise assessment between SNPs in miRNA and RSA.
In conclusion, the current meta-analysis suggested a strong association between miR499a rs3746444 A>G, miR-149 rs2292832 T>C, miR-125a rs41275794 G>A and miR-10a rs3809783 A>T and RSA risk. Thus, these SNPs might be recommended as a predictor for susceptibility to RSA. However, the results of the present meta-analysis should be interpreted carefully because of the heterogeneity among study designs. To obtain a more scientific result, more relevant case-control studies with multiple sample sources must be conducted and included in the meta-analysis.
Acknowledgements
Not applicable.
Funding
Funding: No funding was received.
Availability of data and materials
The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
XW and JG conceived the study. XW and YX searched the databases and extracted the data. XW, YW, CZ and ZD analyzed and interpreted the data. XW wrote the draft of the paper. JG and ZD reviewed the manuscript. XW and JG confirm the authenticity of all the raw data. All authors read and approved the final manuscript.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
References
|
Rai R and Regan L: Recurrent miscarriage. Lancet. 368:601–611. 2006.PubMed/NCBI View Article : Google Scholar | |
|
El Hachem H, Crepaux V, May-Panloup P, Descamps P, Legendre G and Bouet PE: Recurrent pregnancy loss: Current perspectives. Int J Womens Health. 9:331–345. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Jaslow CR, Carney JL and Kutteh WH: Diagnostic factors identified in 1020 women with two versus three or more recurrent pregnancy losses. Fertil Steril. 93:1234–1243. 2010.PubMed/NCBI View Article : Google Scholar | |
|
Garrido-Gimenez C and Alijotas-Reig J: Recurrent miscarriage: Causes, evaluation and management. Postgrad Med J. 91:151–162. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Bartel DP and Chen CZ: Micromanagers of gene expression: The potentially widespread influence of metazoan microRNAs. Nat Rev Genet. 5:396–400. 2004.PubMed/NCBI View Article : Google Scholar | |
|
Lewis BP, Burge CB and Bartel DP: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 120:15–20. 2005.PubMed/NCBI View Article : Google Scholar | |
|
Zhu Y, Lu H, Huo Z, Ma Z, Dang J, Dang W, Pan L, Chen J and Zhong H: MicroRNA-16 inhibits feto-maternal angiogenesis and causes recurrent spontaneous abortion by targeting vascular endothelial growth factor. Sci Rep. 6(35536)2016.PubMed/NCBI View Article : Google Scholar | |
|
Chen X, Guo DY, Yin TL and Yang J: Non-coding RNAs regulate placental trophoblast function and participate in recurrent abortion. Front Pharmacol. 12(646521)2021.PubMed/NCBI View Article : Google Scholar | |
|
Zhu XX, Liu HP, Zhang Z, Wei R, Zhou XB, Wang ZX, Zhao L, Guo Q, Zhang YH, Chu C, et al: MiR-103 protects from recurrent spontaneous abortion via inhibiting STAT1 mediated M1 macrophage polarization. Int J Biol Sci. 16:2248–2264. 2020.PubMed/NCBI View Article : Google Scholar | |
|
Bartel DP: Micrornas: Genomics, biogenesis, mechanism, and function. Cell. 116:281–297. 2004.PubMed/NCBI View Article : Google Scholar | |
|
Lagos-Quintana M, Rauhut R, Lendeckel W and Tuschl T: Identification of novel genes coding for small expressed RNAs. Science. 294:853–858. 2001.PubMed/NCBI View Article : Google Scholar | |
|
Lu J, Getz G, Miska EA, Alvarez-Saavedra E, Lamb J, Peck D, Sweet-Cordero A, Ebert BL, Mak RH, Ferrando AA, et al: MicroRNA expression profiles classify human cancers. Nature. 435:834–838. 2005.PubMed/NCBI View Article : Google Scholar | |
|
Hu Y, Liu CM, Qi L, He TZ, Shi-Guo L, Hao CJ, Cui Y, Zhang N, Xia HF and Ma X: Two common SNPs in pri-miR-125a alter the mature miRNA expression and associate with recurrent pregnancy loss in a Han-Chinese population. RNA Biol. 8:861–872. 2011.PubMed/NCBI View Article : Google Scholar | |
|
Alipour M, Abtin M, Hosseinzadeh A and Maleki M: Association between miR-146a C >G, miR-149 T >C, miR-196a2 T >C, and miR-499 A >G polymorphisms and susceptibility to idiopathic recurrent pregnancy loss. J Assist Reprod Genet. 36:2237–2244. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Amin-Beidokhti M, Mirfakhraie R, Zare-Karizi S and Karamoddin F: The role of parental microRNA alleles in recurrent pregnancy loss: An association study. Reprod Biomed Online. 34:325–330. 2017.PubMed/NCBI View Article : Google Scholar | |
|
Babakhanzadeh E, Danaei H, Abedinzadeh M, Ashrafzadeh HR and Ghasemi N: Association of miR-146a and miR196a2 genotype with susceptibility to idiopathic recurrent pregnancy loss in Iranian women: A case-control study. Int J Reprod Biomed. 19:725–732. 2020.PubMed/NCBI View Article : Google Scholar | |
|
Fazli M and Ghorbian S: Association study of noncoding RNA miR-499 and miR196a2 gene polymorphisms with the risk of idiopathic recurrent pregnancy loss. Gene Cell Tissue. 5(e67253)2018. | |
|
Hu Y, Huo ZH, Liu CM, Liu SG, Zhang N, Yin KL, Qi L, Ma X and Xia HF: Functional study of one nucleotide mutation in pri-miR-125a coding region which related to recurrent pregnancy loss. PLoS One. 9(e114781)2014.PubMed/NCBI View Article : Google Scholar | |
|
Jeon YJ, Choi YS, Rah H, Kim SY, Choi DH, Cha SH, Shin JE, Shim SH, Lee WS and Kim NK: Association study of microRNA polymorphisms with risk of idiopathic recurrent spontaneous abortion in Korean women. Gene. 494:168–173. 2012.PubMed/NCBI View Article : Google Scholar | |
|
Lee JY, Kim JO, Park HS, Ryu CS, Kim JH, Kim YR, Lee WS, Lee JR and Kim NK: Study of the association between microRNA (miR-25T >C, miR-32C >A, miR-125C >T, and miR-222G >T) polymorphisms and the risk of recurrent pregnancy loss in Korean women. Genes (Basel). 11(354)2020.PubMed/NCBI View Article : Google Scholar | |
|
Li Y, Wang XQ, Zhang L, Lv XD, Su X, Tian S, Liu CM, Ma X and Xia HF: A SNP in pri-miR-10a is associated with recurrent spontaneous abortion in a Han-Chinese population. Oncotarget. 7:8208–8222. 2016.PubMed/NCBI View Article : Google Scholar | |
|
Manzoor U, Pandith AA, Amin I, Wani S, Sanadhya D, Lone TA, Mir H, Paray BA, Gulnaz A, Anwar I, et al: Implications of decreased expression of miR-125a with respect to its variant allele in the pathogenesis of recurrent pregnancy loss: A study in a high incidence zone. J Clin Med. 11(3834)2022.PubMed/NCBI View Article : Google Scholar | |
|
Parveen F and Agrawal S: Recurrent miscarriage and micro-RNA among north Indian women. Reprod Sci. 22:410–415. 2015.PubMed/NCBI View Article : Google Scholar | |
|
Rah H, Chung KW, Ko KH, Kim ES, Kim JO, Sakong JH, Kim JH, Lee WS and Kim NK: miR-27a and miR-449b polymorphisms associated with a risk of idiopathic recurrent pregnancy loss. PLoS One. 12(e0177160)2017.PubMed/NCBI View Article : Google Scholar | |
|
Shaker M, Shalabi T, Gaber K and Amr K: Association of miRNA-27a and leptin polymorphisms with recurrent pregnancy loss in Egyptian women. Meta Gene. 24(100617)2019. | |
|
Vahedi SN, Kheirkhah B, Malekirad AA and Hosseini SM: Association of selected polymorphisms in GPX4, COMT, pre-miR-125a, pre-miR-10a, and pre-miR-323b genes in Iranian women with idiopathic recurrent pregnancy loss: A case-control study. Int J Reprod Biomed. 20:111–122. 2022.PubMed/NCBI View Article : Google Scholar | |
|
Wang CY, Wang SG, Wang JL, Zhou LY, Liu HJ and Wang YF: Effect of miRNA-27a and leptin polymorphisms on risk of recurrent spontaneous abortion. Med Sci Monit. 22:3514–3522. 2016.PubMed/NCBI View Article : Google Scholar | |
|
Wang XQ, Li Y, Su X, Zhang L, Liu CM, Liu H, Ma X and Xia H: Haplotype-based association of two SNPs in miR-323b with unexplained recurrent spontaneous abortion in a Chinese Han population. J Cell Physiol. 233:6001–6017. 2018.PubMed/NCBI View Article : Google Scholar | |
|
Wang XQ, Wang H, Zhang L, Liu HN, Gao J, Wang YY, Ma X and Xia HF: Haplotype-based association of two SNPs in miR-423 with unexplained recurrent pregnancy loss in a Chinese Han population. Exp Cell Res. 374:210–220. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Wang X, Zhang L, Guan C, Dong Y, Liu H, Ma X and Xia H: The polymorphism of rs11614913 TT in pri-miR-196a-2 alters the miRNA expression and associates with recurrent spontaneous abortion in a Han-Chinese population. Am J Transl Res. 12:1928–1941. 2020.PubMed/NCBI | |
|
Srivastava P, Bamba C, Chopra S and Mandal K: Role of miRNA polymorphism in recurrent pregnancy loss: A systematic review and meta-analysis. Biomark Med. 16:101–115. 2022.PubMed/NCBI View Article : Google Scholar | |
|
Luchini C, Stubbs B, Solmi M and Veronese N: Assessing the quality of studies in meta-analyses: Advantages and limitations of the Newcastle Ottawa Scale. World J Meta-Anal. 5:80–84. 2017. | |
|
Bagos PG and Nikolopoulos GK: A method for meta-analysis of case-control genetic association studies using logistic regression. Stat Appl Genet Mol Biol. 6(Article 17)2007.PubMed/NCBI View Article : Google Scholar | |
|
Cho SH, Chung KW, Kim JO, Jang H, Yoo JK, Choi Y, Ko JJ, Kim JH, Nishi Y, Yanase T, et al: Association of miR-146aC>G, miR-149C>T, miR-196a2T>C, and miR-499A>G polymorphisms with risk of recurrent implantation failure in Korean women. Eur J Obstet Gynecol Reprod Biol. 202:14–19. 2016.PubMed/NCBI View Article : Google Scholar | |
|
Park HS, Kim ES, Ahn EH, Kim JO, An HJ, Kim JH, Lee Y, Lee WS, Kim YR and Kim NK: The microRNA polymorphisms inmiR-150 and miR-1179 are associated with risk of idiopathic recurrent pregnancy loss. Reprod Biomed Online. 39:187–195. 2019.PubMed/NCBI View Article : Google Scholar | |
|
Salimi S, Sargazi S, Abghari AZ, Nia MH, Ghasemi M and Keikha N: Functional miR29a polymorphism is associated with protection against recurrent spontaneous abortion: A case-control study and bioinformatics analysis. Gene Reports. 23(1011108)2021. | |
|
Shakarami F, Mirfakhraie R, Karizi SZ and Zare H: MIR17HG gene polymorphism and the risk of recurrent spontaneous abortion. Gene Cell Tissue. 3(e34526)2016. | |
|
Salimi S and Sargazi S, Mollashahi B, Nia MH, Mirinejad S, Majidpour M, Ghasemi M and Sargazi S: Association of polymorphisms in miR146a, an inflammation-associated MicroRNA, with the risk of idiopathic recurrent spontaneous miscarriage: A case-control study. Dis Markers. 2022(1495082)2022.PubMed/NCBI View Article : Google Scholar | |
|
Stavros S, Mavrogianni D, Ntetsika L and Drakakis P: Association of IL1B-511T>C, IL6-634G>C, IL-6-174G>C, miR-149 T>C AND miR-27aA>G gene polymorphisms with recurrent pregnancy loss risk in greek population. HJOG. 21:15–24. 2022. | |
|
Murakami A, Ishida S, Thurlow J, Revest JM and Dickson C: SOX6 binds CtBP2 to repress transcription from the Fgf-3 promoter. Nucleic Acids Res. 29:3347–3355. 2001.PubMed/NCBI View Article : Google Scholar | |
|
Kamachi Y, Uchikawa M and Kondoh H: Pairing SOX off: With partners in the regulation of embryonic development. Trends Genet. 16:182–187. 2000.PubMed/NCBI View Article : Google Scholar | |
|
Jazdzewski K, Murray EL, Franssila K, Jarzab B, Schoenberg DR and de la Chapelle A: Common SNP in pre-miR-146a decreases mature miR expression and predisposes to papillary thyroid carcinoma. Proc Natl Acad Sci USA. 105:7269–7274. 2008.PubMed/NCBI View Article : Google Scholar | |
|
Ramkaran P, Khan S, Phulukdaree A, Moodley D and Chuturgoon AA: miR-146a polymorphism influences levels of miR-146a, IRAK-1, and TRAF-6 in young patients with coronary artery disease. Cell Biochem Biophys. 68:259–266. 2014.PubMed/NCBI View Article : Google Scholar | |
|
Suzuki Y, Kim HW, Ashraf M and Haider HK: Diazoxide potentiates mesenchymal stem cell survival via NF-kappaB-dependent miR-146a expression by targeting Fas. Am J Physiol Heart Circ Physiol. 299:H1077–H1082. 2010.PubMed/NCBI View Article : Google Scholar | |
|
Panzan MQ, Mattar R, Maganhin CC, dos Santos Simões R, Rossi AG, da Motta EL, Baracat EC and Soares JM Jr: Evaluation of FAS and caspase-3 in the endometrial tissue of patients with idiopathic infertility and recurrent pregnancy loss. Eur J Obstet Gynecol Reprod Biol. 167:47–52. 2013.PubMed/NCBI View Article : Google Scholar | |
|
Carcagno AL, Marazita MC, Ogara MF, Ceruti JM, Sonzogni SV, Scassa ME, Giono LE and Cánepa ET: E2F1-mediated upregulation of p19INK4d determines its periodic expression during cell cycle and regulates cellular proliferation. PLoS One. 6(e21938)2011.PubMed/NCBI View Article : Google Scholar |
