Genetic association between microRNA gene polymorphisms and polycystic ovary syndrome susceptibility: A systematic review and meta-analysis.

ATBS, KLST, ASBL, DSD and JCOC designed the study. ATBS and KLST searched the literature and extracted the data. ATBS and KSM performed statistical analyses. ATBS and ACAS realized the assessment of risk of bias. ATBS, KLST, ASBL, RNC and AKG. ATBS, RNC, AKG and JCOC critically revised successive drafts of the manuscript. All authors contributed to data analysis and manuscript revision, read and approved the publication of the final version.

This research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES—Finance Code 001).

The initial database search identified 75 studies. After accounting for additional sources from references and gray literature, we removed 44 duplicates, leaving 31 studies for title and abstract screening. Following this, 24 studies were excluded based on the criteria. Seven studies qualified for a full‐text review, and two were subsequently excluded due to insufficient data. Ultimately, five studies 21 , 22 , 23 , 24 , 25 met the inclusion criteria and were included in the qualitative and quantitative synthesis, as illustrated in the PRISMA flow chart (Figure  1 ). PRISMA flow chart of the study selection procedure. The selected studies, detailed in Table  1 , were published between 2017 and 2022 and involved women from Iran 21 , 22 , 23 of Persian ethnicity and Saudi Arabia 24 , 25 of Arabic ethnicity. Across these studies, 985 PCOS patients were included, with a mean age of 26.8–31.2 years. Most studies used the Rotterdam 2004 diagnostic criteria for PCOS, 22 , 23 , 24 , 25 while Ebrahimi et al. 21 used the NIH criteria. The control group consisted of 1004 healthy women, with a mean age ranging from 27.0 to 28.6 years. In the case group, the mean BMI ranged from 23.23 to 27.79, while in the control group, it ranged from 22.92 to 26.1. Characteristics of included studies. miR‐126 miR‐146a miR‐196a‐2 miR‐499 miR‐126 rs4636297 (G>A) miR‐146a rs2910164 (G>C) miR‐196a‐2 rs11614913 (C>T) miR‐499 rs3746444 (T>C) miR‐27a miR‐196a‐2 miR‐423 miR‐27a rs895819 (A>G) miR‐196a‐2 rs11614913 (C>T) miR‐423 rs6505162 (C>A) Note : BMI, calculated as weight in kilograms divided by the square of height in meters. Abbreviation: BMI, body mass index. HWE was assessed for the control group in each study. Most polymorphisms met HWE criteria, except for those reported by Ebrahimi et al. 21 and Hosseini et al. 22 Across the five case–control studies, seven miRNA polymorphisms were evaluated for their potential association with PCOS. Each study focused on different miRNA polymorphisms: miR‐222 rs2858060 (G>C), 22 miR‐126 rs4636297 (G>A), 23 miR‐499 rs3746444 (T>C), 23 miR‐27a rs895819 (A>G), 24 miR‐423 rs6505162 (C>A), 24 miR‐196a‐2 rs11614913 (T>G), 23 , 24 and miR‐146a rs2910164 (C>G). 21 , 22 , 23 , 25 The genotypic distribution of miRNA gene polymorphisms is shown in Table  2 . For miR‐27a rs895819, Mir et al. 24 reported that among PCOS cases, the GG genotype had the lowest frequency ( n  = 10), followed by the AA genotype ( n  = 40), while the GA genotype was the most frequent ( n  = 55). In controls, the AA genotype predominated ( n  = 60). For miR‐423 rs6505162, the CA genotype was the most prevalent in both the control group ( n  = 59) and the case group ( n  = 62). Li et al. 23 analyzed miR‐126 rs4636297 and miR‐499 rs3746444, finding the heterozygous GA genotype to be most common among both cases ( n  = 184) and controls ( n  = 236), with GG being less frequent. In the case of miR‐499 rs3746444, the TT genotype was marginally more common among cases ( n  = 134) than controls ( n  = 188), while the heterozygous TC genotype was more frequent in controls. Hosseini et al. 22 evaluated the miR‐222 rs2858060 polymorphism and reported that the GC genotype was most prevalent among both cases and controls, with frequencies of 134 in cases and 107 in controls. Distributions of microRNA gene polymorphism genotypes. Abbreviation: HWE, Hardy–Weinberg equilibrium. Both miR‐196a‐2 rs11614913 and miR‐146a rs2910164 were investigated in multiple studies. The CC genotype of miR‐196a‐2 rs11614913 was the most frequent among both cases and controls. Li et al. 23 reported that 38 cases had the CC genotype compared to controls ( n  = 39), while the CT genotype was more frequent among cases ( n  = 49). miR‐146a rs2910164 was widely analyzed across studies. 21 , 22 , 23 , 25 The GC genotype was more common in cases ( n  = 381) than in controls ( n  = 273), whereas the GG genotype was more frequent in controls ( n  = 560) compared to cases ( n  = 381). The Newcastle‐Ottawa Scale was used to evaluate study quality, with most studies scoring seven out of nine (Table  3 ). The most common limitation observed was in the selection domain, where studies lacked representativeness in case selection. Quality assessment of included research papers using the Newcastle‐Ottawa Scale. We performed quantitative synthesis only for miRNAs analyzed in more than one study, focusing on miR‐196a‐2 rs11614913 (T>G) and miR‐146a rs2910164 (C>G). Two studies, totaling 500 PCOS cases and 500 controls, examined the association of miR‐196a‐2 rs11614913 with PCOS. 23 , 24 Notably, the TT genotype was significantly associated with an increased risk of PCOS (OR 1.57, 95% CI: 1.09–2.27, I 2  = 0%, P  = 0.02), whereas the CC genotype was associated with a reduced risk of PCOS (OR 0.76, 95% CI: 0.59–0.98, I 2  = 75%, P  = 0.03). In contrast, no statistically significant associations were found for the CT (OR 1.06, 95% CI: 0.82–1.36, I 2  = 82%, P  = 0.66) genotypes, with high heterogeneity for these findings. Our pooled analysis involving four studies 21 , 22 , 23 , 25 demonstrated a significant association between the miR‐146a rs2910164 polymorphism and PCOS risk. The pooled OR was 0.44 (95% CI: 0.36–0.54, I 2  = 0%, P  < 0.00001), indicating a protective association between the GG genotype and PCOS (Figure  2 ). Analysis of the GC genotype yielded a pooled OR of 1.77 (95% CI: 1.45–2.16, I 2  = 0%, P  < 0.00001), suggesting a 77% increased likelihood of PCOS in individuals with this genotype. The CC genotype also showed a significant association, with a pooled OR of 2.18 (95% CI: 1.54–3.07, I 2  = 0%, P  G) polymorphism with risk of polycystic ovary syndrome based on overall analysis. (a) GG genotype; (b) GC genotype; (c) CC genotype. Table  4 summarizes the evidence certainty for the critical outcomes based on the GRADE approach. Both outcomes were rated as very low certainty due to biases, inconsistency, and publication bias, as indicated by the heterogeneity analysis. GRADE assessment. 500 cases 500 controls (2 non‐randomized studies) 870 cases 889 controls (4 non‐randomized studies) Abbreviations: CI, confidence interval; GRADE, grading of recommendations assessment, development, and evaluation; OR, odds ratio. Egger's linear regression test detected significant publication bias ( P  < 0.05).

This meta‐analysis reviewed case–control studies investigating the association of miRNA SNPs with PCOS. Among seven miRNA SNPs studied, meta‐analyses were conducted specifically on miR‐146a rs2910164 and miR‐196a‐2 rs11614913. Based on data from 870 PCOS patients and 889 healthy controls, the GG genotype of miR‐146a rs2910164 was significantly associated with a protective effect against PCOS, while the GC and CC genotypes were linked to increased risk. Conversely, the TT genotype of miR‐196a‐2 rs11614913 was associated with a heightened risk of PCOS. However, the evidence supporting these findings was of low certainty, indicating that the true effect might differ from the observed estimates. The miR‐146a gene is critical in PCOS pathogenesis due to its role in regulating steroid hormone secretion, which influences levels of progesterone, estradiol, and testosterone. 26 These hormonal imbalances contribute to the menstrual irregularity's characteristic of PCOS. Studies consistently report aberrant miR‐146a expression in women with PCOS, including findings by Long et al. 27 demonstrating upregulated miR‐146a levels negatively correlated with serum testosterone. Elevated miR‐146a‐5p levels have been further associated with anovulation and insulin resistance. 28 , 29 We propose that the rs2910164 polymorphism in miR‐146a may influence disease susceptibility through its regulatory effects on gene expression. The G allele, associated with lower miR‐146a expression, 30 may protect against PCOS by mitigating inflammatory and hormonal disruptions, whereas the C allele, linked to increased miR‐146a expression, 30 may exacerbate disease risk by promoting TNF‐α production. 31 Elevated TNF‐α levels contribute to insulin resistance, hyperandrogenism, and obesity, all of which are hallmarks of PCOS. 32 Interestingly, the C allele has been linked to increased miR‐146a expression in ovarian granulosa cells, correlating with apoptosis—an important mechanism underlying defective follicular development in PCOS. 33 These findings align with research in breast and ovarian cancer, where high miR‐146a expression is associated with the C allele. 34 On the other hand, the GG genotype of miR‐146a is associated with an increased risk of ovarian cancer compared to the CC genotype in Chinese women, 35 which is reinforced by studies showing that lower levels of miR‐146a in primary tumor tissue samples correlate with shorter progression‐free survival in ovarian cancer patients, 36 considering their tumor suppressor effect highlighting the multifaceted role of miR‐146a in reproductive and metabolic health. Additionally, the miR‐196a‐2 rs11614913 polymorphism affects the maturation of pre‐miRNA, with the T allele linked to lower synthesis of mature miR‐196a2. 37 In our analysis, the TT genotype was significantly associated with increased PCOS risk. This SNP has also been implicated in conditions such as endometriosis, 38 recurrent pregnancy loss, 39 and endometrial and ovarian cancer, 40 underscoring its relevance to female reproductive health. The C allele, associated with higher miR‐196a2 expression, promotes cellular viability and migration in ovarian cells. 37 Although the C allele has been linked to cardiovascular diseases 41 and type 2 diabetes mellitus (T2DM), 42 conditions closely related to PCOS. Our pooled analysis showed that the CC genotype was significantly associated with a reduced risk of PCOS. This finding suggests that, although the C allele has been linked to other metabolic disorders, it may play a protective role in PCOS. However, demographic factors such as ethnicity, age, and BMI may influence genotype distribution and modulate disease risk. Furthermore, there are conflicting results regarding the role of the rs11614913 gene variation in female reproductive conditions. While the rs11614913 SNP has been linked to idiopathic recurrent abortion in Korean women, 43 no such association was found in Iranian women. 44 Similarly, combined genotypes, such as miR‐146a CG/miR‐196a2 TC, have shown protective effects against clinical phenotypes of premature ovarian failure 45 and pre‐eclampsia, 46 highlighting the nuanced role of miRNA variants in disease pathogenesis. This is the first comprehensive meta‐analysis to assess the association between miRNA polymorphisms and PCOS risk. Nonetheless, several limitations should be acknowledged. Most included studies involved Persian and Arabian populations, which restricts the generalizability of the findings. Two studies had control groups deviating from Hardy–Weinberg equilibrium, suggesting possible genotyping errors or population stratification. The limited dataset hindered subgroup analyses by BMI, age, and clinical PCOS phenotypes. Inconsistent genotype reporting also precludes stratification by genetic models (e.g., dominant, recessive, codominant). Additionally, the small number of studies reduced the statistical power and the reliability of publication bias assessment using the Egger's test. According to the GRADE criteria, the overall certainty of evidence was low to very low, warranting cautious interpretation of the results.

This meta‐analysis provides evidence that the homozygous GG genotype of miR‐146a rs2910164 appears to confer a protective effect, while the GC and CC genotypes, as well as the TT genotype of miR‐196a‐2 rs11614913, increase PCOS risk. These findings suggest potential roles for miRNA polymorphisms as biomarkers. Further large‐scale multiethnic studies are necessary to confirm these associations and clarify the mechanisms by which miRNA SNPs contribute to PCOS pathogenesis, as current evidence is rated as low to very low certainty according to the GRADE.

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder among women of reproductive age and the leading cause of anovulatory infertility. 1 , 2 , 3 It is characterized by chronic anovulation, hyperandrogenism, and menstrual irregularities, often accompanied by obesity, insulin resistance, and elevated luteinizing hormone (LH) levels. 4 Women with PCOS are at an increased risk of developing insulin resistance, diabetes, cardiovascular complications, and cancers involving the ovaries, uterus, and breasts. 4 The exact etiology of PCOS remains unclear, though it is believed to result from complex interactions between genetic and environmental factors contributing to its onset and progression. 5 Genetic variations, particularly in specific loci, may predict an individual's susceptibility to PCOS. Research efforts are increasingly directed toward identifying potential candidate genes and single‐nucleotide polymorphisms (SNPs) associated with the condition to improve early diagnostic capabilities. MicroRNAs (miRNAs), a class of small non‐coding RNAs, regulate approximately one‐third of human protein‐coding genes and play crucial roles in cellular proliferation, apoptosis, differentiation, immune response, and inflammation. 6 , 7 By acting at the post‐transcriptional level through translational repression and messenger RNA (mRNA) decay, miRNAs influence key cellular functions, including cell division, differentiation, and death. 8 , 9 In ovarian follicle development, including follicle growth and ovulation, miRNAs are particularly critical. 10 Emerging evidence suggests that aberrant miRNA expression is associated with PCOS. Elevated miRNA levels have been observed in affected individuals, potentially distinguishing them from healthy controls. 11 , 12 These findings underscore the potential of miRNAs as non‐invasive biomarkers for early PCOS diagnosis due to their stability, resistance to nucleases, and ease of detection. Additionally, SNPs are common in the human genome and can influence disease risk. SNPs within miRNA genes, in particular, may alter miRNA expression or maturation, affecting their regulatory roles. 13 Such polymorphisms can disrupt miRNA‐mediated cellular functions, potentially influencing PCOS development and progression. 14 Although some studies have investigated the association of miRNA gene SNPs with gynecologic and reproductive conditions, 15 , 16 few have specifically explored their impact on PCOS. Systematic reviews play a critical role in synthesizing and evaluating the strength of existing evidence. Thus, this study aims to conduct a systematic review and meta‐analysis to assess the association between miRNA gene polymorphisms and PCOS risk, offering insights into potential biomarkers and therapeutic targets for the condition.

The authors have no conflicts of interest.

This systematic review and meta‐analysis protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (registration no.: CRD42024542478). The review followed the guidelines established by the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) 17 and the Meta‐analysis of Observational Studies in Epidemiology (MOOSE) 18 groups. To be eligible for inclusion, studies had to meet the following criteria: (i) Assess the association between miRNA gene polymorphisms and PCOS, (ii) provide genotype distributions necessary for calculating odds ratios (ORs) and 95% confidence intervals (CIs), and (iii) use a case–control design. The research question was structured according to the population, concept and context (PCC) format: Participants: women clinically diagnosed with PCOS by Rotterdam or National Institute of Health (NIH) criteria; Concept: miRNA gene polymorphisms increase or decrease PCOS risk; Context: case–control studies. Participants: women clinically diagnosed with PCOS by Rotterdam or National Institute of Health (NIH) criteria; Concept: miRNA gene polymorphisms increase or decrease PCOS risk; Context: case–control studies. Abstracts, editorials, letters, review papers, and case reports; duplicate or overlapping publications; and studies lacking detailed genotype distribution data were excluded. Databases searched included PubMed, Embase, Web of Science, and Scopus. A pilot search strategy was initially developed for PubMed and subsequently adapted for other databases, with systematic reviews and meta‐analyses on related topics included to identify additional studies. The search period was from inception up to September 2024, and no restrictions were imposed on publication year or language. The MeSH (medical subject heading) terms and keywords included “MicroRNAs” AND “Polymorphism, Single Nucleotide” AND “Polycystic Ovary Syndrome”. The search strategies for each database are detailed in Table  S1 . Search results were imported into Rayyan software for duplicate removal, and an initial screening of 50 studies was conducted by two researchers (ATBS and KLST) to standardize selection criteria. Following this calibration, titles and abstracts of all identified studies were independently screened. Discrepancies were resolved through discussion or, if necessary, by a third researcher (JCOC). The same process was applied to the full‐text screening of selected studies. Data extraction was conducted using a form in Excel based on variables of interest. A pilot extraction was performed to ensure consistency, with two investigators (DSD and KSM) cross‐verifying the extracted data. Extracted information included the first author's name, publication year, study design, sample size, mean age, ethnicity, body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters), genotype distributions, and Hardy–Weinberg equilibrium (HWE). Corresponding authors were contacted for missing data when necessary. Two researchers (ATBS and ACAS) independently assessed methodologic quality and risk of bias in the included studies using the Newcastle‐Ottawa Scale (NOS), a validated tool for evaluating nonrandomized studies in systematic reviews. 19 Studies were assessed across three domains: selection, comparability, and exposure, with scores above seven points indicating high‐quality studies. Discrepancies were resolved by consensus or by a third reviewer (AKG). Meta‐analysis was conducted for miRNA polymorphisms examined in more than one study. Statistical analyses were performed using Review Manager (RevMan) software, version 5.4 (The Cochrane Collaboration, Copenhagen, Denmark). ORs with 95% CIs were calculated for each genotype to assess associations with PCOS. A Mantel–Haenszel fixed‐effects model was used if no significant heterogeneity was found, while a random‐effects model was applied if substantial heterogeneity was detected. Heterogeneity was assessed using the Chi‐square ( χ 2 ) test and quantified with the I 2 statistic, with I 2 values of 25%, 50%, and 75% indicating low, moderate, and high heterogeneity, respectively. Subgroup analyses explored genotype‐specific effects, with forest plots displaying individual study estimates alongside pooled estimates. Egger's test was used to assess publication bias. The grading of recommendations, assessment, development, and evaluations (GRADE) method was employed to rate the certainty of evidence for each outcome as high, moderate, low, or very low, based on factors such as risk of bias, indirectness, inconsistency, imprecision, and publication bias. 20

Table S1. Table S2.