Polycystic ovary syndrome (PCOS), the most common endocrinopathy in reproductive-aged women of reproductive age, is characterized by hyperandrogenism, ovulatory dysfunction and infertility, with a prevalence up to 12% to 18% depending on diagnostic criteria like clinical hyperandrogenism, oligoanovulation and polycystic ovaries. The syndrome is linked to metabolic disorders, such as insulin resistance, obesity, and diabetes. Etiology of PCOS remains largely unknown, however, complex polygenic disorder with environment and individual were believed the prominent contributing factors. Additionally, several studies have report a high risk of premature coronary artery disease (CAD) in patients with PCOS. Genetic factors such as vitamin B12 and folate are involved in the regulation of homocysteine (Hcy) metabolism pathway which related to CAD in PCOS. Methylenetetrahydrofolate reductase (MTHFR) plays an essential role in folate metabolism, DNA methylation, and RNA synthesis.[7–8] By regulating enzymatic activity, MTHFR catalyzes the conversion of 5, 10-methylenetetrahydrofolate into 5- methylenetetrahydrofolate irreversibly which is the main form of folic acid in plasma and tissues. Low folate concentrations also tend to be correlated with raised plasma Hcy levels as it is a cofactor in the re-methylation of Hcy. Reduced activity of MTHFR is the most common cause of hyper Hcy. This makes MTHFR an important gene for investigation in PCOS as decreased efficiency of folate/Hcy pathway could increase the risk. Single gene polymorphisms in the MTHFR gene can change the expression and activity of the protein it encodes. Among them, The C677T polymorphism is the most common one which results in a variant of MTHFR enzyme and increase circulating total Hcy levels at a homozygous state.[11,12]
Up to now, a total of 20 epidemiological studies have evaluated the association between the MTHFR gene polymorphism C677T and risk of PCOS in diverse ethnicities.[13–31] However, the results have been inconsistent. Five meta-analyses have summarized the associations between MTHFR gene polymorphism C677T and risk of PCOS come to opposite conclusions.[22,32–35] The main factor that would contribute to the discrepancy is that the previous metaanalyzes with relatively small sample size may lead to a lower statistical power. Since that data, several more studies have emerged. Therefore, we aimed to perform an updated metaanalysis to investigate the associations between MTHFR gene polymorphism C677T and risk of PCOS in order to get a more precise and reliable assessment of the association.
2.1 Search strategy
To identify eligible studies for this metaanalysis, PubMed (http://www.ncbi.nlm.nih.gov/pubmed/), Embase (http://www.embase.com), WanFang and the Chinese National Knowledge Infrastructure databases were used to retrieve articles up to up to October 28, 2019 without any language limitation. The following terms and keywords were used: “MTHFR” (or “methylenetetrahydrofolate reductase”), “polymorphism” (or “variant”) and “PCOS” (or “polycystic ovary syndrome”). We have also manually searched the reference lists of the retrieved articles for potential papers. Ethical approval is not necessary since this study is a metaanalysis.
2.2 Selection criteria
The included studies met the following inclusion criteria:
- (1) Full-text publications;
- (2) The association between MTHFR gene polymorphism C677T and risk of PCOS was examined based on case-control design;
- (3) Provide sufficient data about MTHFR C677T genotypes and genotype distributions to estimate the odds ratio (OR) with 95% confidence intervals (95% CI); Studies that met the exclusion criteria were excluded if they were overlapped data, reviews, reports, comments, letters, and so on.
2.3 Data extraction
The data from all eligible studies were extracted by 2 authors independently (Li and Zhu). The following information was extracted: first author, year of publication, country, ethnicity, source of controls, total sample size, genotype frequencies in cases and controls, P-value for Hardy-Weinberg equilibrium (HWE), genotyping methods.
2.4 Statistical analysis
Analyzes were calculated using Stata software version 12.0 (Stata Corp., College Sta-tion, TX) and all P values were 2-sided. The pooled ORs and 95% CI were used to assess the strength of association between MTHFR C677T polymorphism and PCOS under 4 genetic models, including allele model (T vs C), dominant model (TT+CT vs CC), recessive model (TT vs CT+CC) and homozygous model (TT vs CC). The significance of pooled ORs was examined by Z-test, and P < .05 was considered as statistically significant. Heterogeneity assumption was checked by Cochran Q-statistic and I2 statistic test was calculated to quantify the proportion of the total variation across studies due to heterogeneity. Subgroup analysis was also performed by ethnicity, etiologies, genotype methods and source of controls to investigate the possibility of heterogeneity. The fixed-effects model (the Mantel–Haenszel method) is used when the effects are assumed to be homogenous (P > .05 of Q test and I2 < 50%). Otherwise, the random effects model (the Der Simonian and Laird method) is used when they are P < .05 of Q test and I2 > 50%.[37,38] The Chi-squared test was used to calculated HWE of the genotype frequencies of controls. A value of P < .05signified a departure from HWE. Sensitivity analysis was performed to examine stability of our results by omitting each study in each turn. Publication bias was measured by funnel plots and quantified by the Begg and Egger tests (significance level was set at 0.05).
3.1 Study characteristics
Our search identified 18 studies including 2196 cases and 2201 controls from15 publications relevant to the role of MTHFR C677T polymorphism on PCOS susceptibility. Two publications[17,22] respectively included 2 and 3 different diseases which giving 5 studies altogether (Fig. 1). Table 1 describes the detailed characteristics of each studies included in our metaanalysis.
3.2 Meta-analysis results and heterogeneity analysis
The findings with regard to association between MTHFR C677T polymorphism and PCOS risk are presented in Table 2. For the overall analysis, our metaanalysis revealed a significant main effects on PCOS risk in 3 genetic models (allele model: OR = 1.40, 95% CI = 1.27–1.53; dominant model: OR = 1.47, 95% CI = 1.17–1.85); homozygous model: OR = 1.90, 95% CI = 1.55–2.32) (Fig. 2-A;B;D). The results of different ethnic subgroups were also found positive correlations among Asians (allele model: OR = 1.48, 95% CI = 1.33–1.64; dominant model: OR = 1.57, 95% CI = 1.23–1.99; recessive model: OR = 1.51, 95% CI = 1.25–1.83; homozygous model: OR = 2.15, 95% CI = 1.71–2.69) and Turkey population (allele model: OR = 1.89, 95% CI = 1.18–3.03; dominant model: OR = 2.96, 95% CI = 1.49–5.90) (Fig. 2-A;B;D), but no significant associations were found in all Caucasians genetic models (Fig. 2-A;B;C;D). In further stratified analysis by HWE, a significant association was observed in studies in HWE in three genetic models (allele model: OR = 1.34, 95% CI = 1.15–1.98; dominant model: OR = 1.49, 95% CI = 1.16–1.93; recessive model: OR = 1.55, 95% CI = 1.29–1.85; homozygous model: OR = 2.55, 95% CI = 1.66–2.84). In addition, significant effect on genotype method of polymerase chain reaction (PCR), restriction fragment length polymorphism in all genetic models and real-time PCR in allele models, PCR- ligase detection reaction (LDR) in three genetic models. However, no significant elevated risks of Bio-Rad variant under all models. Furthermore, we also found significant risks in the stratified analysis by source of controls.
Subgroup analysis by ethnicity, genotype methods, source of controls and HWE was conducted to detect sources of heterogeneity. And we found significant heterogeneity under the recessive model might be related to the Caucasian subjects, studies not in HWE, genotype method of Bio-Rad Variant,TaqMan,Squencing (P < .05).
3.3 Sensitivity analyses
We performed a sensitivity analysis by deletion of 1 single study at a time to explore the influence of each individual study on the overall pooled ORs. And the estimate of results was not influenced excessively by omitting any single study under the allele model (T vs C) of MTHFR C677T (Fig. 3), which indicated that the results of our metaanalysis were statistically reliable.
3.4 Publication bias
The Begg rank correlation and Egger linear regression tests were conducted to access the publication bias. The funnel plots of Begg test seemed to show no evident asymmetry (Fig. 4), further validated by Egger test (P > .05).
At present, epidemiological literature regarding the effect of PCOS as a risk factor for MTHFR C677T gene polymorphism remains inconsistent and inconclusive. Five metaanalyses have summarized the associations, Bagos PG et al (2009) and Lee et al (2014) concluded a negative result based on 6 and 9 eligible studies respectively, similarly, S. Justin Carlus et al suggested that MTHFR C677T was not clinically important in PCOS in most of the populations based on 13 studies. However, Li-yuan Fu et al in their meta-analysis of 10 studies indicated that the 677T allele increases PCOS susceptibility, and its seems to be more intense in Europeans than in Asians. More recently, in 2017 Lihong Wang et al suggested that the T allele is strongly associated with the risks for PCOS in the Middle Eastern populations while protective in Caucasian populations. Nevertheless, the credibility of Lihong Wang analysis should be re-examined as some eligible studies have been left out. While in our meta-analysis, which was based on collecting 7 more studies than previous analyses, we found that T allele likely had an increased PCOS risk compared with the C allele, and the association was more pronounced in the Asians and Turkey population but not in Caucasians, suggesting genetic diversity among different ethnicities. Further studies need to evaluate the association of MTHFR C677T polymorphism with PCOS in Turkish populations as only 1 study on a Turkish population.
In the subgroup analysis by HWE, we demonstrated a significant association in studies in HWE but negative results in studies not in HWE. Combined with sensitivity analysis we can find that the studies showing deviation from the HWE influenced the results of meta-analysis but not significantly, as small size of controls not in HWE. Likewise, we detected similar significant association in subgroup analysis for genotype methods and source of controls. The statistical significance of MTHFR C677T polymorphism with PCOS risk suggesting that this polymorphism may be a potential biomarker which have been expected to make early diagnosis, predict patient outcome, or direct optimal therapy for the individual patient.
There are still some limitations in interpreting the current results. First, the interactions between gene-gene, gene-environment, and even different polymorphic loci of the same gene may modulate POCS risk, as there is no original data for further analysis in our included studies, which limited our evaluation of potential interactions. Second, in the stratified analysis by ethnicity and genotype method, only 1 study was included in Turkey population, Bio-Rad Variant and PCR-LDR method, the limited sample sizes might weaken the metaanalysis results. Finally, there is the potential for publication bias, as no attempts were made to identify unpublished articles and only studies in English or Chinese were included in this analysis.
In conclusion, this meta-analysis demonstrates that the T-allele of MTHFR C677T polymorphism contribute to an increased risk of PCOS, especially among Asians but not Caucasians. Larger sample sizes study with more detailed individual data of gene-gene and functional studies on MTHFR C677T polymorphism are needed to strengthen our current results.
Conceptualization: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Data curation: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Formal analysis: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Funding acquisition: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Investigation: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Methodology: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Project administration: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Resources: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Software: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Supervision: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Validation: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Visualization: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Writing – original draft: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
Writing – review & editing: Yin Li, Hongqiu Zhu, Min Liu, Zhulan Zeng, Yanling Zeng, Xinlei Xu, Min Ye.
. Brettenthaler N, De Geyter C, Huber PR, et al. Effect of the insulin sensitizer pioglitazone on insulin resistance, hyperandrogenism, and ovulatory dysfunction in women with polycystic ovary syndrome. J Clin Endocrinol Metab 2004;89:3835–40.
. March WA, Moore VM, Willson KJ, et al. The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Hum Reprod 2010;25:544–51.
. Sam S. Adiposity and metabolic dysfunction in polycystic ovary syndrome. Horm Mol Biol Clin Investig 2015;21:107–16.
. Talbott EO, Zborowskii JV, Boudraux MY. Do women with polycystic ovary syndrome have an increased risk of cardiovascular disease? Review of the evidence. Minerva Ginecol 2004;56:27–39.
. Urbanek M, Kosova G. Genetics of the polycystic ovary syndrome. Mol Cell Endocrinol 2013;373:29–38.
. Wierzbicki AS. Homocysteine and cardiovascular disease: a review of the evidence. Diab Vasc Dis Res 2007;4:143–50.
. Bai JL, Zheng MH, Xia X, et al. MTHFR C677T polymorphism
contributes to prostate cancer risk among Caucasians: a meta-analysis of 3511 cases and 2762 controls. Eur J Cancer 2009;45:1443–9.
. Muslumanoglu MH, Tepeli E, Demir S, et al. The analysis of the relationship between A1298C and C677T polymorphisms of the MTHFR gene with prostate cancer in Eskisehir population. Genet Test Mol Biomarkers 2009;13:641–5.
. Goyette P, Frosst P, Rosenblatt DS, et al. Seven novel mutations in the methylenetetrahydrofolate reductase gene and genotype/phenotype correlations in severe methylenetetrahydrofolate reductase deficiency. Am J Hum Genet 1995;56:1052–9.
. Jacques V, Desreux JF. Complexation of Thorium(IV) and Uranium(IV) by a Hexaacetic Hexaaza Macrocycle: kinetic and thermodynamic topomers of actinide chelates with a large cavity ligand. Inorg Chem 1996;35:7205–10.
. Tawakol A, Omland T, Gerhard M, et al. Hyperhomocysteinemia is associated with impaired endothelium-dependent vasodilatation in humans. Circulation 1997;9:1119–21.
. Herrmann W. The importance of hyperhomocysteinemia as a risk factor for diseases: an overview. Clin Chem Lab Med 2001;39:666–74.
. Glueck CJ, Wang P, Fontaine RN, et al. Plasminogen activator inhibitor activity: an independent risk factor for the high miscarriage rate during pregnancy in women with polycystic ovary syndrome. Metabolism 1999;48:1589–95.
. Sills ES, Genton MG, Perloe M, et al. Plasma homocysteine, fasting insulin, and androgen patterns among women with polycystic ovaries and infertility. J Obstet Gynaecol Res 2001;27:163–8.
. Tsanadis G, Vartholomatos G, Korkontzelos I, et al. Polycystic ovarian syndrome and thrombophilia. Hum Reprod 2002;17:314–9.
. Orio F Jr, Palomba S, Di Biase S, et al. Homocysteine levels and C677T polymorphism
of methylenetetrahydrofolate reductase in women with polycystic ovary syndrome. J Clin Endocrinol Metab 2003;88:673–9.
. Palep-Singh M, Picton HM, Yates ZR, et al. Polycystic ovary syndrome and the single nucleotide polymorphisms of methylenetetrahydrofolate reductase: a pilot observational study. Hum Fertil 2007;10:33–41.
. Choi SW, Gu BH, Ramakrishna S, et al. Association between a single nucleotide polymorphism
in MTHFR gene and polycystic ovary syndrome. Eur J Obstet Gynecol Reprod Biol 2009;145:85–8.
. Karadeniz M, Erdogan M, Zengi A, et al. Methylenetetrahydrofolate reductase C677T gene polymorphism
in Turkish patients with polycystic ovary syndrome. Endocrine 2010;38:127–33.
. Jain M, Pandey P, Tiwary NK, et al. MTHFR C677T polymorphism
is associated with hyperlipidemia in women with polycystic ovary syndrome. J Hum Reprod Sci 2012;5:52–6.
. Idali F, Zareii S, Mohammad-Zadeh A, et al. Plasminogen activator inhibitor 1 and methylenetetrahydrofolate reductase gene mutations in iranian women with polycystic ovary syndrome. Am J Reprod Immunol 2012;68:400–7.
. Justin Carlus S, Saumya Sarkar, Sandeep Kumar Bansa, et al. Is MTHFR 677 C>T polymorphism
clinically important in polycystic ovarian syndrome (PCOS)? A case-control study meta-analysis and trial sequential analysis. PLoS One 2016;11:e0151510.
. Naghavi A, Mozdarani H, Garshasbi M, et al. Prevalence of methylenetetrahydrofolate reductase C677T polymorphism
in women with polycystic ovary syndrome in southeast of Iran. J Med Life 2015;8((Spec Iss 3)):229–32.
. Qi Q, Zhang H, Yu M, et al. Association of methylenetetrahydrofolate reductase gene polymorphisms with polycystic ovary syndrome. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 2015;32:400–4.
. Ożegowska K, Bogacz A, Bartkowiak-Wieczorek J, et al. Is there an association between the development of metabolic syndrome in PCOS patients and the C677T MTHFR gene polymorphism
? Ginekol Pol 2016;87:246–53.
. Wu JB, Zhai JF, Yang J. Role of methylenetetrahydrofolate reductase C677T and A1298C polymorphisms in polycystic ovary syndrome risk. Genet Mol Res 2016;15(4.):
. Jiao X, Chen W, Zhang J, et al. Variant alleles of the ESR1, PPARG, HMGA2, and MTHFR genes are associated with polycystic ovary syndrome risk in a chinese population: a case-control study. Front Endocrinol 2018;9:504.
. Kazerooni T, Ghaffarpasand F, Asadi N, et al. Correlation between thrombophilia and recurrent pregnancy loss in patients with polycystic ovary syndrome: a comparative study. J Chinese Med Assoc 2013;76:282–8.
. Szafarowska M, Segiet A, Jerzak MM. Methylenotetrahydrololate reductase A1298C and C677T polymorphisms and adverse pregnancy outcome in women with PCOS. Neuro Endocrinl Lett 2016;37:141–6.
. Jiang Y, Lu Y, Li Y, et al. Study on the correlation between methylene tetrahydrofolate reductase gene polymorphism
and polycystic ovary syndrome. Matern Child Heal Care China 2015;30:3831–3.
. Geng J, Zhang C, Hu S, et al. Role of methylenetetrahydrofolate reductase genetic polymorphisms in polycystic ovary syndrome risk. Int J Clin Exp Pathol 2016;9:8532–7.
. Bagos PG. Plasminogen activator inhibitor-1 4G/5G and 5,10-methylene-tetrahydrofolate reductase C677T polymorphisms in polycystic ovary syndrome. Mol Hum Reprod 2009;15:19–26.
. Fu LY, Dai LM, Li XG, et al. Association of methylenetetrahydrofolate reductase gene C677T polymorphism
with polycystic ovary syndrome risk: a systematic review and meta-analysis update. Eur J Obstet Gynecol Reprod Biol 2014;172:56–61.
. Lee YH, Song GG. Plasminogen activator inhibitor-1 4G/5G and the MTHFR 677C/T polymorphisms and susceptibility to polycystic ovary syndrome: a meta-analysis. Eur J Obstet Gynecol Reprod Biol 2014;175:8–14.
. Lihong Wang, Wenting Xu, Caihong Wang, et al. Methylenetetrahydrofolate reductase C677T polymorphism
and the risks of polycystic ovary syndrome: an updated meta-analysis of 14 studies. Oncotarget 2017;8:59509–17.
. Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta-analyses. BMJ 2003;327:557–60.
. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospec-tive studies of disease. J Natl Cancer Inst 1959;22:719–48.
. DerSimonian R, Laird NM. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177–88.