Literature DB >> 32639550

Methylenetetrahydrofolate reductase gene polymorphisms in the risk of polycystic ovary syndrome and ovarian cancer.

Ying Xiong1, Ce Bian1, Xiaojuan Lin1, Xiaoli Wang1, Kehui Xu1, Xia Zhao1.   

Abstract

Polymorphisms of methylenetetrahydrofolate reductase (MTHFR) in hormone metabolism pathways might cause metabolic disturbances and contribute to the development of polycystic ovary syndrome (PCOS) and ovarian cancer, but the published studies were inconsistent. The aim of the present study was to evaluate the MTHFR C677T (rs1801133) and A1298C (rs1801131) gene polymorphisms in the risk of PCOS and ovarian cancer by meta-analysis. A comprehensive electronic search was conducted in databases for studies published from 1995 to 2020. The pooled ORs were calculated by Revman 5.2 software. Twenty-nine articles including 45 case-control studies were included. We found that MTHFR C677T polymorphisms were correlated with elevated PCOS risk (TT vs. CT+CC: OR = 1.41, 95%CI = 1.20-1.67; TT+CT vs. CC: OR = 1.54, 95%CI = 1.07-2.22; CT vs. CC+TT: OR = 1.18, 95%CI 1.04-1.33; TT vs. CC: OR = 1.47, 95%CI = 1.03-2.11; T vs. C: OR = 1.25, 95%CI = 1.06-1.47), which were more obvious in Middle Eastern subgroup. MTHFR A1298C polymorphisms were also associated with overall PCOS susceptibility (CC vs. AC+AA: OR = 2.55, 95% CI = 1.61-4.03; CC+AC vs. AA: OR = 1.84, 95%CI = 1.04-3.28; CC vs. AA: OR = 2.66, 95%CI = 1.68-4.22; C vs. A: OR = 1.67, 95%CI = 1.03-2.71), which were mainly reflected in Asian subjects. For ovarian cancer, MTHFR C677T polymorphisms were only related with elevated ovarian cancer risk in Asian population, while no significant association was found for A1298C polymorphisms. This meta-analysis suggested that MTHFR C677T and MTHFR A1298C polymorphisms were correlated with elevated PCOS risk. MTHFR C667T only posed a higher risk for ovarian cancer in Asians instead of other populations, while MTHFR A1298C polymorphisms were not related to ovarian cancer risk. Further studies are needed to validate the conclusion.
© 2020 The Author(s).

Entities:  

Keywords:  meta-analysis; methylenetetrahydrofolate reductase; ovarian cancer; polycystic ovary syndrome; polymorphism; variant

Mesh:

Substances:

Year:  2020        PMID: 32639550      PMCID: PMC7369393          DOI: 10.1042/BSR20200995

Source DB:  PubMed          Journal:  Biosci Rep        ISSN: 0144-8463            Impact factor:   3.840


Introduction

Polycystic ovary syndrome (PCOS) is one of the most common endocrine malfunctions, reportedly affecting 5–10% of reproductive age women [1]. According to the Rotterdam consensus in 2003, PCOS is featured with oligo- or anovulation, hyperandrogenism and polycystic ovaries [2]. Clinical manifestations of PCOS may include menstrual irregularities, signs of androgen excess, obesity and insulin resistance, with increased risk of Type 2 diabetes and cardiovascular events [3-5]. PCOS impairs female fertility to varying degrees, which remains to be the leading cause for medical assistance. The relationship between PCOS and ovarian cancer has long been controversial. PCOS has been hypothesized to increase ovarian cancer risk through increased androgen exposure in pre-clinical studies [6,7]. Several case–control studies also explored the association of PCOS with ovarian cancer risk, while a recent meta-analysis concluded that there was an increased ovarian cancer risk observed in PCOS population by pooling three individual studies (OR = 1.4; 95% CI = 0.9–2.2) [8]. However, later studies reported no association between self-reported PCOS and ovarian cancer risk. Meanwhile, several studies proposed that an elevation in cancer risk might be relevant to only certain histological subtypes [9,10]. With emerging genetic findings such as homologous repair deficiency in gynecologic malignancies, more and more attention was focused on the genetic root of both diseases. Existing clinical studies suggest that both genetic background and environmental factors with a cluster of metabolic disturbances might contribute to the development of PCOS and ovarian cancer [11,12]. It was also suggested that if the mutation of critical genes in the hormone metabolism pathways could contribute to both diseases individually. It might give us the hint on the pathophysiologic relationship between PCOS and ovarian malignancies. Take homocysteine (Hcy) as an example, it is a sulfur-containing amino acid derived from methionine metabolism and has been proved to be related with insulin resistance and increased risk of cardiovascular diseases in PCOS patients. Elevated plasma level of homocysteine is caused by its deficient transformation, including its transmethylation to methionine, which is regulated by methylenetetrahydrofolate reductase (MTHFR). The MTHFR is an enzyme involved in folate metabolism, and mutations of MTHFR gene would result in reduced activity of the enzyme, thus increasing total Hcy levels in plasma [13,14]. Several gene abnormalities of MTHFR have been explored and two types of SNPs have been found. One is at base position 677 (rs1801133), a C-to-T transition (an alanine to valine substitution). The other is at base position 1298 (rs1801131), an A-to-C transition (a glutamate-to-alanine substitution). It is estimated that approximately 10–15% of Caucasians are homozygous for the TT genotype at positions 677, which is more common in Hispanics (25%) and least common in individuals of African descent (6%) [15]. Another study reported that the overall frequency of the 677TT genotype and 1298CC genotype in the Chinese Han population was 23.2% and 3.9%, respectively [16]. In 1999, Gleuck first reported the association between MTHFR C677T polymorphisms and PCOS, ever since several similar researches have been conducted [17]. In 2014, two independent meta-analyses were published to explore the relationship between MTHFR C677T polymorphisms and PCOS risk but with controversial conclusions [18,19]. One reason of inconsistent conclusions is that neither of the two studies included all current published data. Also, one study categorized subjects from Middle Eastern countries as Caucasian, which might affect the subgroup analysis. Similarly, a certain amount of case–control studies explored the relationship between MTHFR polymorphisms and ovarian cancer. However, the results were conflicting and inconclusive, presumably due to small sample size in each published study while possible selection bias such as ethnicity was unignorable [20,21]. Therefore, in the present study, we conducted a comprehensive meta-analysis by collecting the existing published data to better clarify MTHFR C677T and A1298C polymorphisms in the risk of PCOS and ovarian cancer.

Materials and methods

Search for eligible literature

A comprehensive electronic search was performed using PubMed, Embase, Medline (Ovid), Weipu, CNKI and Wanfang databases for studies published from March 1995 to February 2020. The following subject terms and keywords were used: “methylenetetrahydrofolate reductase”, “MTHFR”, “PCOS”, “polycystic ovarian syndrome”, “ovarian cancer” “polymorphism”, “variant” and “mutation”. The search was updated every week until February 20, 2020.

Inclusion and exclusion criteria

Articles fulfilling the following criteria were included: (i) studied the MTHFR C677T and A1298C polymorphisms in PCOS or ovarian cancer patients, (ii) provided sufficient data in both case and control groups to calculate the odds ratios (ORs) and the corresponding 95% confidence intervals (95% CIs), (iii) mentioned specific diagnostic criteria for PCOS (the NIH criteria or the Rotterdam criteria) and described patients’ symptoms in details, (iv) case–control studies. When duplicate data were present in different articles, only the latest one would be taken into consideration. In addition, Newcastle–Ottawa Scale (NOS) was used to assess the quality of the observational studies included. Three aspects of selection, comparability, and exposure (nine scores in total) were carefully assessed. Studies of moderate or high quality were included (score of 5 or higher). As such, articles that didn’t fulfill the criteria mentioned above were excluded.

Data extraction

All potential studies were investigated by two independent viewers. The following items were extracted: first author, year of publication, ethnicity, matched parameters, target genotypes, genotyping methods, participant numbers and genotype distributions in cases and controls. Any discrepancies were resolved by discussion with a third reviewer until a consensus was reached.

Statistical analysis

Meta-analyses were undertaken using the Revman 5.2 softer ware (Cochrane Collaboration, Copenhagen) to calculate the pooled ORs and corresponding 95% CIs. SNPs of MTHFR C677T and A1298C were considered as binary variables. Different contrast models were judged: (i) homozygous mutants contrast, (ii) homozygous and heterozygous mutants contrast, (iii) heterozygous mutants contrast, (iv) homozygous mutants contrast in homozygotes, (v) mutant allelic contrast. Besides the overall comparisons, we also performed subgroup analyses stratified by ethnicities in consideration of population differences. Heterogeneity assumptions were tested using Higgins Itest. When the Ivalue was less than 50%, a fixed-effects model was used otherwise a random-effects model was applied. The Z test was performed to determine the significance of the pooled ORs where P less than 0.05 was considered statistically significant. The presence of publication bias was evaluated by visually inspecting the asymmetry in funnel plots and Egger’s test. All statistical analyses were performed using Revman 5.2 software (Cochrane Collaboration, Copenhagen, Denmark) except the Egger’s test, which was conducted using STATA 14.0 (StataCorp LP, College Station, TX, U.S.A.).

Results

Search results

After primary search, 178 results were retrieved. In our further review, 129 articles were not related to MTHFR polymorphisms and PCOS risk by reading titles and abstracts and thus were excluded. 11 articles focused on MTHFR polymorphisms in different diseases or complication of PCOS like thrombophilia and pregnancy loss. Five studies estimated genetic variants other than C677T and A1298C. Four articles were excluded for non-case–control studies such as meta-analysis and lab research (Figure 1). Among the remaining 29 enrolled articles, 25 were of moderate quality (NOS score of 6 or 7) and 4 were of high quality (NOS score of 8 or 9) therefore were all included in this meta-analysis. By reviewing the genotype counts, 9 articles were found to focus on both C677T and A1298C thus were considered as 18 separate studies. Two articles discussed two different ethnicities thus separate ethnicities were considered as individual studies. One article genotyped subjects from three independent studies and were considered as three studies. Therefore, 45 studies were enrolled for this meta-analysis. We also summarized matched parameters in both case and control groups as shown in Table 1 [17,22-49].
Figure 1

The flow chart of study selection

Table 1

Characteristics of included studies

First authorYearEthnicityStudy diseaseMTHFR polymorphismGenotyping methodMatched parametersStudy quality (NOS)
Carlus2016AsianPCOSC667TPCR-RFLPAge, height, weight, LH, glucose, BMI, LH/FSH8
Choi2009AsianPCOSC667TPCR-RFLPBMI, weight, waist/hip ratio, FSH, estradiol, prolactin7
Geng2016AsianPCOSC667T, A1298CPCR-RFLPAge, FSH, prolactin, estradiol6
Glueck1999CaucasianPCOSC667T, A1298CPCR-RFLPAge, race7
Idali2012Middle EasternPCOSC667TPCR-RFLPUnknown6
Jain2012AsianPCOSC667TPCR-RFLPAge, FSH, TSH, prolactin7
Jiang2015AsianPCOSC667T, A1298CPCR-RFLPAge6
Jiao2018AsianPCOSC667TPCR-RFLPAge, estradiol6
Karadeniz2010Middle EasternPCOSC667TPCR-RFLPAge, BMI, estradiol, DHEA-S, TSH, prolactin, total cholesterol, triglyceride, LDL-cholesterol8
Lee2003AsianPCOSC667TPCR-RFLPUnknown6
Naghavi2015Middle EasternPCOSC667TPCR-RFLPAge, race6
Orio2003CaucasianPCOSC667TPCR-RFLPAge, BMI, waist/hip ratio, FSH, prolactin, vitamin B12, folate, homocysteine, fasting glucose7
Ozegowska2016CaucasianPCOSC667TPCR-RFLPAge, waist/hip ratio, fasting glucose, LDL-C, HDL-C, cholesterol/HDL, SBP, DBP7
Palep-Singh2007Asian& CaucasianPCOSC667T, A1298CPCR-RFLPSouth Asian: age, FSH, insulin, cholesterol, LDL. Caucasian: birth weight, waist/hip ratio, right ovarian volume, FSH, testosterone, cholesterol, triglyceride, LDL
Qi2015East AsianPCOSC667T, A1298CPCR-RFLPVitamin B12, homocysteine6
Sills2001CaucasianPCOSC667TPCR-RFLPAge, fasting glucose, androstenedione, DHEA-S, homocysteine7
Szafarowska2016CaucasianPCOSC667T, A1298CPCR-RFLPHomocysteine, AMH6
Tsanadis2002CaucasianPCOSC667TPCR-RFLPAge, BMI, DHEA-S, glucose7
Wu2016AsianPCOSC667T, A1298CPCR-RFLPAge, prolactin, FSH, estradiol, triglyceride7
Gao2012AsianOCC667TPCR-RFLPAge, BMI, tobacco smoking, alcohol use, menopausal status7
Jakubowska2012CaucasianOCC667TPCR-RFLPAge, BMI6
Ozkilic2016Middle EasternOCC667TPCR-RFLPAge6
Pawlik2011CaucasianOCC667TPCR-RFLPAge, BMI, FSH, LH, estradiol6
Prasad2011AsianOCC667TMassARRAYUnknown6
Song2012AsianOCA1298CPCR-RFLPAge, tobacco use, alcohol use, menopausal status7
Terry2010CaucasianOCC667T, A1298CTaqManAge, oral contraceptive use, liveborn number7
Webb2011CaucasianOCC667T, A1298CPCR-PFLPAge, BMI, oral contraceptive use, energy intake7
Wu2007AsianOCC667TNAAge, BMI6
Zhang2012AsianOCC667TPCR-RFLPTobacco use, alcohol use, menopausal status, hormone replacement therapy8

Abbreviations: AMH, Anti-Müllerian hormone; BMI, body mass index; DHEA-S, dehydroepiandrosterone sulfate; FSH, follicle-stimulating hormone; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; LH, luteinizing hormone; MTHFR, methylenetetrahydrofolate reductase; NOS, Newcastle–Ottawa scale; OC, ovarian cancer; PCOS, polycystic ovary syndrome; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; TSH, thyroid-stimulating hormone.

Abbreviations: AMH, Anti-Müllerian hormone; BMI, body mass index; DHEA-S, dehydroepiandrosterone sulfate; FSH, follicle-stimulating hormone; HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; LH, luteinizing hormone; MTHFR, methylenetetrahydrofolate reductase; NOS, Newcastle–Ottawa scale; OC, ovarian cancer; PCOS, polycystic ovary syndrome; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; TSH, thyroid-stimulating hormone.

MTHFR C677T polymorphisms in PCOS

As shown in Tables 2 and 4, the variant allele T has a significant association with the risk of PCOS compared with allele C (T vs. C: OR = 1.25, 95%CI = 1.06–1.47) in random effect model (I 64%) by pooling 9614 alleles together. In consistent with this, significant association was also found in T containing genotypes (TT+CT or TT) and TT genotypes alone (TT+CT vs. CC: OR = 1.54, 95%CI = 1.07–2.22; TT vs. CC: OR = 1.47, 95%CI = 1.03–2.11; TT vs. CT+CC: OR = 1.41, 95%CI = 1.20–1.67) among 4807 participants (Figure 2A). Interestingly, when comparing heterozygous CT with homozygous TT+CC, the pooled ORs again showed statistical significance (CT vs. CC+TT: OR = 1.18, 95%CI = 1.04–1.33). This indicates that C677T was correlated with elevated risk of PCOS, both in homozygous individuals and heterozygous mutants. Subgroup meta-analyses in stratified ethnicities showed that C677T mutant Middle Eastern population contained higher PCOS risk (TT+CT vs. CC: OR = 2.66, 95%CI = 1.54–4.58; CT vs. CC+TT: OR = 2.64, 95%CI = 1.27–5.49; TT vs. CC: OR = 2.21, 95%CI = 1.16–4.21; T vs. C: OR = 1.82, 95%CI = 1.39–2.37), though only 602 participants were included. No similar tendency was displayed in Asian or Caucasian population.
Table 2

Genotype distributions in cases and controls for MTHFR C677T and A1298C polymorphisms in PCOS

AuthorYearCountryPolymorphismCaseControl
AAAaaaAAAaaa
Carlus#2016AsianC677T7716083161
Carlus2016AsianC677T132333126291
Choi2009AsianC677T6712535336715
Geng2016AsianC677T5179541029638
Glueck1999CaucasianC677T142341198926
Idali2012Middle EasternC677T1719266259
Jain2012AsianC677T7616082130
Jiang2015AsianC677T133740135653
Jiao2018AsianC677T521621229613972
Karadeniz2010EasternC677T1565635287
Lee2003AsianC677T33467275221
Naghavi2015Middle EasternC677T613813136519
Orio2003CaucasianC677T164113173815
Ozegowska2016CaucasianC677T87522953379
Palep-Singh*2007AsianC677T1470900
Palep-Singh2007CaucasianC677T1112210151
Qi2015AsianC677T146041212314
Sills2001CaucasianC677T2592891
Szafarowska2016CaucasianC677T3339419307
Tsanadis2002CaucasianC677T1214420196
Wu2016AsianC677T941064412210431
Geng2016AsianA1298C1045714157709
Idali2012EasternA1298C122069460
Jiang2015AsianA1298C6624098231
Palep-Singh2007AsianA1298C993072
Palep-Singh*2007CaucasianA1298C141011051
Qi2015AsianA1298C7139543141
Szafarowaska2016CaucasianA1298C40261034175
Wu2016AsianA1298C1437724166847

‘A’ represents wild-type allele and ‘a’ represents mutant allele.

Study separately enrolled two sub-populations of Indian and were thus considered as two studies.

Study separately enrolled Asian and Caucasian and were thus considered as two studies.

Table 4

Summary of different comparative results for MTHFR C677T polymorphisms in PCOS

GenotypesOverall and subgroupParticipantsOR and 95%CIZ valueP valueI2 (%)Effect model#
TT vs. CT+ CCOverall4,8071.41 [1.20, 1.67]4.050.0142F
Asian3,2111.38 [0.99, 1.92]1.920.0555R
Caucasian9941.09 [0.72, 1.65]0.390.70F
Middle Eastern6021.13 [0.39, 3.32]0.230.8260R
TT+ CT vs. CCOverall4,8071.54 [1.07, 2.22]2.310.0285R
Asian3,2111.76 [0.99, 3.13]1.620.0590R
Caucasian9941.03 [0.78, 1.36]0.210.8429F
Middle Eastern6022.66 [1.54, 4.58]3.520.0153R
CT vs. CC+ TTOverall4,8071.18 [1.04, 1.33]2.640.0149F
Asian3,2111.10 [0.95, 1.27]1.250.210F
Caucasian9940.99 [0.75, 1.31]0.050.9640F
Middle Eastern6022.64 [1.27, 5.49]2.60.0174R
TT vs. CCOverall2,8721.47 [1.03, 2.11]2.10.0459R
Asian1,9291.58 [0.92, 2.72]1.670.0975R
Caucasian5671.14 [0.72, 1.81]0.580.560F
Middle Eastern3762.21 [1.16, 4.21]2.410.020F
T vs. COverall9,6141.25 [1.06, 1.47]0.640.0164R
Asian6,4221.27 [1.01, 1.61]2.030.0474R
Caucasian1,9881.04 [0.85, 1.27]0.340.7319F
Middle Eastern1,2041.82 [1.39, 2.37]4.380.010F

Effect model includes fixed-effect model (F) and random-effect model (R).

Figure 2

Representative forest plots

(A) TT vs. CT+CC for MTHFR C667T polymorphisms in PCOS. (B) CC vs. AC+AA for A1298C polymorphisms in PCOS. (C) TT vs. CT+CC for MTHFR C667T polymorphisms in ovarian cancer. (D) CC vs. AC+AA for A1298C polymorphisms in ovarian cancer.

Representative forest plots

(A) TT vs. CT+CC for MTHFR C667T polymorphisms in PCOS. (B) CC vs. AC+AA for A1298C polymorphisms in PCOS. (C) TT vs. CT+CC for MTHFR C667T polymorphisms in ovarian cancer. (D) CC vs. AC+AA for A1298C polymorphisms in ovarian cancer. ‘A’ represents wild-type allele and ‘a’ represents mutant allele. Study separately enrolled two sub-populations of Indian and were thus considered as two studies. Study separately enrolled Asian and Caucasian and were thus considered as two studies.

MTHFR A1298C polymorphisms in PCOS

The result of the association between MTHFR A1298C and PCOS risk was as followed. About 7 articles including 8 studies with 784 PCOS patients and 854 healthy controls were pooled. Except the heterozygous mutant comparison that presented an insignificant OR, others showed significant outcome between A1298C mutation and elevated PCOS risk (CC vs. AC+AA: OR = 2.55, 95% = 1.61–4.03; CC+AC vs. AA: OR = 1.84, 95%CI = 1.04–3.28; CC vs. AA: OR = 2.66, 95%CI = 1.68–4.22; C vs. A: OR = 1.67, 95%CI = 1.03–2.71) (Figure 2B). When stratified by ethnicity, only Asians shared consistent results with the overall population (CC vs. AC+AA: OR = 2.46, 95% = 1.44–4.22; CC+AC vs. AA: OR = 1.33, 95%CI = 1.05–1.67; CC vs. AA: OR = 2.43, 95%CI = 1.41–4.18; C vs. A: OR = 1.39, 95%CI = 1.14–1.69). Notably, fixed-effect model was conducted in both Asian and Caucasian comparisons but random-effect model was used for overall population. This might suggest the consistency among the same ethnicity but differences among different populations might exist. The above data indicated that MTHFR A1298C posed a higher risk for PCOS in overall population, particularly in Asians instead of other populations. The detailed results were summarized in Tables 2 and 5.
Table 5

Summary of different comparative results for MTHFR A1298C polymorphisms in PCOS

GenotypesOverall and subgroupParticipantsOR and 95%CIZ valueP valueI2 (%)Effect model#
CC vs. AC+AAOverall1,6382.55 [1.61, 4.03]3.980.0126F
Asian1,3272.46 [1.44, 4.22]3.280.016F
Caucasian1731.37 [0.48, 3.90]0.590.550F
CC+AC vs. AAOverall1,6381.84 [1.04, 3.28]2.090.0481R
Asian1,3271.33 [1.05, 1.67]2.40.0214F
Caucasian1731.37 [0.74, 2.54]1.010.310F
AC vs. AA+CCOverall1,6381.52 [0.89, 2.57]1.540.1278R
Asian1,3271.11 [0.88, 1.41]0.870.3934F
Caucasian1731.25 [0.66, 2.39]0.690.490F
CC vs. AAOverall1,1502.66 [1.68, 4.22]4.150.0149F
Asian9232.43 [1.41, 4.18]3.20.0139F
Caucasian1151.51 [0.52, 4.42]0.750.450F
C vs. AOverall3,2761.67 [1.03, 2.71]2.070.0483R
Asian2,6541.39 [1.14, 1.69]3.30.0134F
Caucasian3461.31 [0.80, 2.14]1.080.280F

Effect model includes fixed-effect model (F) and random-effect model (R).

MTHFR C677T and A1298C polymorphisms in ovarian cancer

Genetic distributions and pooled ORs were shown in Tables 3 and 6. Eleven studies including 12,700 participants were evaluated for C677T polymorphisms in ovarian cancer risk. While the overall group analysis presented no relationship between C-to-T mutation and ovarian cancer susceptibility (Figure 2C), the stratified group analysis of 1455 Asian subjects indicated an increased cancer risk (TT vs. CT+CC: OR = 2.35, 95%CI = 1.59–3.48; TT+CT vs. CC: OR = 1.49, 95%CI = 1.19–1.86; TT vs. CC: OR = 2.84, 95%CI = 1.88–4.31; T vs. C: OR = 1.49, 95%CI = 1.26–1.77). Since the Asian population only consisted of a minority among the overall group subjects, it should be noted that the overall group conclusion might be changed when sample sizes of different ethnicities vary. In general, MRHFR C677R polymorphisms was associated with increased cancer risk in Asian population.
Table 3

Genotype distributions in cases and controls for MTHFR C677T and A1298C polymorphisms in ovarian cancer

AuthorYearCountryPolymorphismCaseControl
AAAaaaAAAaaa
Gao2012AsianC677T971002723217822
Jakubowska2012CaucasianC677T42344611614471481422
Ozkilic2016Middle EasternC677T1828419305
Pawlik2011CaucasianC677T675513637918
Prasad2011AsianC677T723511681
Terry#2010CaucasianC677T427492140499488138
Terry2010CaucasianC677T71721021021755
Terry2010CaucasianC677T1641673319316851
Webb2011CaucasianC677T744709185571568139
Wu2007AsianC677T174024323513
Zhang2012AsianC677T10294191159211
Song2012AsianA1298C1077716112799
Terry2010CaucasianA1298C51543093534450109
Terry2010CaucasianA1298C68671823620048
Terry2010CaucasianA1298C1731494218918043
Webb2011CaucasianA1298C770693175598561119

‘A’ represents wild-type allele and ‘a’ represents mutant allele.

Study separately genotyped subjects from three studies, the New England Case Control Study (NEC), Nurses’ Health Study (NHS), and Mayo Clinic Ovarian Cancer Case Control Study (MAY), thus were considered as three studies.

Table 6

Summary of different comparative results for MTHFR C677T polymorphisms in ovarian cancer

GenotypesOverall and subgroupParticipantsOR and 95%CIZ valueP valueI2 (%)Effect model#
TT vs. CT+ CCOverall12,7001.11 [0.88, 1.41]0.870.3961R
Asian1,4552.35 [1.59, 3.48]4.30.010F
Caucasian11,1411.82 [0.85, 3.93]0.720.4716F
TT+ CT vs. CCOverall12,7001.06 [0.99, 1.15]1.580.1149F
Asian1,4551.49 [1.19, 1.86]3.440.013F
Caucasian11,1411.02 [0.94, 1.10]0.460.6432F
CT vs. CC+ TTOverall12,7001.05 [0.97, 1.13]1.170.240F
Asian1,4551.11 [0.88, 1.39]0.890.370F
Caucasian11,1411.04 [0.96, 1.13]0.920.3622F
TT vs. CCOverall7,1501.18 [0.89, 1.55]1.160.2468R
Asian9152.84 [1.88, 4.31]4.930.010F
Caucasian6,1990.97 [0.85, 1.11]0.410.6825F
T vs. COverall25,4001.08 [0.96, 1.21]1.310.1966R
Asian2,9101.49 [1.26, 1.77]4.60.0110F
Caucasian22,2821.00 [0.94, 1.06]0129F

Effect model includes fixed-effect model (F) and random-effect model (R).

‘A’ represents wild-type allele and ‘a’ represents mutant allele. Study separately genotyped subjects from three studies, the New England Case Control Study (NEC), Nurses’ Health Study (NHS), and Mayo Clinic Ovarian Cancer Case Control Study (MAY), thus were considered as three studies. Effect model includes fixed-effect model (F) and random-effect model (R). Effect model includes fixed-effect model (F) and random-effect model (R). Effect model includes fixed-effect model (F) and random-effect model (R). The results of MTHFR A1298C polymorphisms in ovarian cancer were straightforward (Figure 2D). The meta-analysis failed to show significant association between variant genotypes (or alleles) and ovarian cancer susceptibility in corresponding effect models, neither in overall group analysis nor Caucasian subgroup analysis (Tables 3 and 7).
Table 7

Summary of different comparative results for MTHFR A1298C polymorphisms in ovarian cancer

GenotypesOverall and subgroupParticipantsOR and 95%CIZ valueP valueI2 (%)Effect model#
CC vs. AC+AAOverall6,8601.09 [0.92, 1.28]1.010.310F
Caucasian6,4601.06 [0.90, 1.26]0.740.460F
CC+AC vs. AAOverall6,8601.00 [0.91, 1.10]0.060.950F
Caucasian6,4600.99 [0.90, 1.09]0.190.850F
AC vs. AA+CCOverall6,8600.97 [0.88, 1.07]0.670.50F
Caucasian6,4600.97 [0.88, 1.07]0.640.520F
CC vs. AAOverall3,9741.08 [0.91, 1.27]0.850.40F
Caucasian3,7301.05 [0.88, 1.25]0.570.570F
C vs. AOverall13,7201.02 [0.94, 1.09]0.410.680F
Caucasian12,9201.01 [0.93, 1.09]0.190.850F

Effect model includes fixed-effect model (F) and random-effect model (R).

Effect model includes fixed-effect model (F) and random-effect model (R).

Publication bias

The shapes of the funnel plots appeared to be symmetrical in all genetic comparisons, indicating the lack of publication bias and the reliability of the meta-analysis in both overall and subgroups (Figure 3). We further performed Egger’s tests in the analyses that proposed significant ORs. The results demonstrated no significant publication bias (P>0.05, data not shown).
Figure 3

Representative funnel plots

(A) TT vs. CT+CC for MTHFR C667T polymorphisms in PCOS. (B) CC vs. AC+AA for A1298C polymorphisms in PCOS. (C) TT vs. CT+CC for MTHFR C667T polymorphisms in ovarian cancer. (D) CC vs. AC+AA for A1298C polymorphisms in ovarian cancer.

Representative funnel plots

(A) TT vs. CT+CC for MTHFR C667T polymorphisms in PCOS. (B) CC vs. AC+AA for A1298C polymorphisms in PCOS. (C) TT vs. CT+CC for MTHFR C667T polymorphisms in ovarian cancer. (D) CC vs. AC+AA for A1298C polymorphisms in ovarian cancer.

Discussion

Polycystic ovary syndrome consists a heterogeneous endocrinological disorder, which is characterized by oligo- or anovulation, hyperandrogenism and polycystic ovaries [50]. These pathophysiological malfunctions are associated with clinical manifestations like oligomenorrhea, amenorrhea, infertility, hirsutism, obesity, acne, Type 2 diabetes mellitus, skin hyperpigmentation, etc [51,52]. The long term of treatments and the consequential infertility seriously affect women’s living qualities, even though many symptoms could be meliorated by oral contraceptive and metformin. Contradictory evidence exists regarding PCOS and risk of ovarian cancer. Some studies suggested that self-reported PCOS was related to higher risk of ovarian cancer when age was adjusted, while others concluded no significant association between the two diseases. Moreover, several studies reported that PCOS might decrease the risk of ovarian cancer because the use of oral contraceptives were common among such patients [53,54]. The etiology of PCOS and ovarian cancer involve multiple genetic and epigenetic alterations that cause changes in metabolic enzymes such as MTHFR. It has been reported that polymorphisms of the MTHFR gene might reduce MTHFR enzyme activity. As a result, the concentration of Hcy in plasma would be increased, which is commonly discovered in PCOS and ovarian cancer patients. Even recently, several trials have explored the efficacy of folate receptor antagonist in ovarian cancer [55]. This clinically reflects the significance of folate metabolic pathways in ovarian carcinogenesis. Therefore, it is assumed that the abnormality (including several polymorphisms) of MTHFR, which is a key component of the folate pathways, could contribute to increased PCOS and ovarian cancer risk. In the present study, we performed an updated meta-analysis to explore MTHFR C667T and A1298C polymorphisms in the PCOS and ovarian cancer risk. Twenty-nine articles including 45 case–control studies were included. We found that MTHFR C677T polymorphisms were correlated with elevated PCOS risk, which were more obvious in Middle Eastern subgroups. Also, MTHFR A1298C polymorphisms were associated with overall PCOS risk, which were mainly reflected in Asians. For ovarian cancer, MTHFR C677T polymorphisms were only related with elevated ovarian cancer risk in Asians, while no significant association was found for A1298C polymorphisms. Several points could be noted based on current results. First, both MTHFR C677T and MTHFR A1298C polymorphisms were correlated with elevated PCOS risk. Although polymorphisms of A1298C seem to be less prevalent than C677T, the current findings suggest that any impairment on folate methylation could impact the development of PCOS, regardless of its frequency [16]. As such, new genetic abnormalities in folate metabolism pathways are of great potential in unrevealing the critical pathogenic factor of PCOS. Second, ethnicity difference seems to have an impact on the disease susceptibility. Despite confounding factors that could not be excluded from the study, such findings may indicate that different genetic components could play different extends of roles in the disease development, leading to different manifestations. For instance, it was reported that East Asian patients with PCOS were more likely to have diabetes compared with Caucasian patients [56]. Thus, continuous genome-based studies are needed to personalize the diagnosis and management of PCOS across different ethnicities. Third, the relationship between MTHFR and ovarian cancer is less conclusive compared with PCOS. While both polymorphisms are associated with increased PCOS risk in overall population, significant result was only observed in MTHFR C667T Asian subgroup for ovarian cancer. PCOS has been hypothesized to increase ovarian cancer risk through androgen exposure in pre-clinical settings and oral contraceptive use has been proved to reduce the risk of ovarian cancer, suggesting the potential metabolic relationship between PCOS and ovarian cancer [57,58]. However, it is hard to conclude a concrete relationship between PCOS and ovarian cancer under the mechanism of MTHFR gene polymorphisms based on the current results. Whereas such findings could not rule out the potential relationship between PCOS and ovarian cancer risk. In a population-based, case–control study of 476 subjects with histologically confirmed epithelial ovarian cancer, Schildkraut et al. found that ovarian cancer risk was found to increase 2.5-fold (95% CI: 1.1–5.9) among women with PCOS [59]. Moreover, the possibility that the pathogenesis of PCOS and ovarian cancer might be interacted on the pathways of hormone metabolism still exist. In fact, recent identification of several proteins overexpressed in both PCOS and ovarian cancer, including calreticulin, fibrinogen, superoxide dismutase, and vimentin gave us a clue on the two diseases and even promising subgroup identification of ovarian cancer based on PCOS development. As such, whether MTHFR polymorphisms played a role in this intriguing contribution remains to be further studied. Despite our efforts to pool the results of currently published studies, some disadvantages of the present meta-analysis still existed. First, the number of enrolled studies was so far the largest among all relevant meta-analysis but was still limited. It is possible that the results of further investigations and unpublished articles might be different from the present conclusion, thus cautions should be paid to explain the results. Second, this meta-analysis was based on unadjusted estimations. Although matched parameters were carefully reviewed, it is known that some unreported risk factors like family history and genetic information (e.g. BRCA mutation, HRD status) were also important in the development of PCOS or ovarian cancer [60]. Meanwhile, no histological subtypes of ovarian cancer were provided in the source studies. Since it is reported that an elevation in ovarian cancer risk might be relevant to only certain histological subtypes [9,10], the absence or enrichment of certain types of ovarian cancer in the present study might not reveal the real-world disease landscape. All those confounding factors mentioned above might affect the validity of the results. In addition, MTHFR polymorphisms and elevated homocysteine levels may increase risks of several other diseases such as thromboembolism, endometrial cancer, hypertension, diabetes, etc. Such conditions themselves may interact with diet, concurrent medication and lifestyle, thus affecting the susceptibility of PCOS and ovarian cancer. Third, we confirmed the risk prone effects of MTHFR polymorphisms in Middle Eastern population for PCOS and particular MTHFR A1298C polymorphisms in Asian population for ovarian cancer. The ethnicities should be deliberately illustrated because of two reasons. One is that the ethnicity distribution in the overall group did not reflect the real-world percentages. The sample size changes due to future publications in Asian population for C667T in ovarian cancer risk might affect the final readout of overall group analysis. The other is that only Turkish and Iranian were included in the Middle Eastern subgroup and most of the stratified Asians were Chinese, while other populations such as Hispanics and Black were not within this discussion. Thus, studies enrolling diverse ethnicities were required.

Conclusion

To our knowledge, the present study was the most updated meta-analysis exploring the association between MTHFR C677T and A1298C polymorphisms and the PCOS and ovarian cancer. It was also the first study to explore the MTHFR polymorphisms in both diseases. Although it was hard to conclude a concrete association between PCOS and ovarian cancer under the mechanism of MTHFR gene polymorphisms, the present study suggested that MTHFR C677T and A1298C polymorphisms were correlated with elevated PCOS risk while MTHFR C677T polymorphisms only posed a higher risk for ovarian cancer in Asians. Further studies are needed to validate the conclusion.
  54 in total

Review 1.  A practical approach to the diagnosis of polycystic ovary syndrome.

Authors:  R Jeffrey Chang
Journal:  Am J Obstet Gynecol       Date:  2004-09       Impact factor: 8.661

2.  Folate and related micronutrients, folate-metabolising genes and risk of ovarian cancer.

Authors:  P M Webb; T I Ibiebele; M C Hughes; J Beesley; J C van der Pols; X Chen; C M Nagle; C J Bain; G Chenevix-Trench
Journal:  Eur J Clin Nutr       Date:  2011-06-01       Impact factor: 4.016

3.  Methylenetetrahydrofolate reductase gene polymorphisms as predictive and prognostic biomarkers in ovarian cancer risk.

Authors:  Song Gao; Ning Liu; Yang Ma; Liu Ying
Journal:  Asian Pac J Cancer Prev       Date:  2012

4.  Long and irregular menstrual cycles, polycystic ovary syndrome, and ovarian cancer risk in a population-based case-control study.

Authors:  H R Harris; L J Titus; D W Cramer; K L Terry
Journal:  Int J Cancer       Date:  2016-10-06       Impact factor: 7.396

5.  Ovarian cancer and oral contraceptives: collaborative reanalysis of data from 45 epidemiological studies including 23,257 women with ovarian cancer and 87,303 controls.

Authors:  V Beral; R Doll; C Hermon; R Peto; G Reeves
Journal:  Lancet       Date:  2008-01-26       Impact factor: 79.321

Review 6.  Obesity, lipids, cardiovascular risk, and androgen excess.

Authors:  R A Wild
Journal:  Am J Med       Date:  1995-01-16       Impact factor: 4.965

Review 7.  Phenotype and genotype of polycystic ovary syndrome in Asia: Ethnic differences.

Authors:  Jin Ju Kim; Young Min Choi
Journal:  J Obstet Gynaecol Res       Date:  2019-10-07       Impact factor: 1.730

Review 8.  Risk of endometrial, ovarian and breast cancer in women with polycystic ovary syndrome: a systematic review and meta-analysis.

Authors:  John A Barry; Mallika M Azizia; Paul J Hardiman
Journal:  Hum Reprod Update       Date:  2014-03-30       Impact factor: 15.610

9.  Is MTHFR 677 C>T Polymorphism Clinically Important in Polycystic Ovarian Syndrome (PCOS)? A Case-Control Study, Meta-Analysis and Trial Sequential Analysis.

Authors:  S Justin Carlus; Saumya Sarkar; Sandeep Kumar Bansal; Vertika Singh; Kiran Singh; Rajesh Kumar Jha; Nirmala Sadasivam; Sri Revathy Sadasivam; P S Gireesha; Kumarasamy Thangaraj; Singh Rajender
Journal:  PLoS One       Date:  2016-03-16       Impact factor: 3.240

10.  ACMG Practice Guideline: lack of evidence for MTHFR polymorphism testing.

Authors:  Scott E Hickey; Cynthia J Curry; Helga V Toriello
Journal:  Genet Med       Date:  2013-01-03       Impact factor: 8.822

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1.  Associations of the MTHFR rs1801133 polymorphism with gastric cancer risk in the Chinese Han population.

Authors:  Zhiqiang Han; Huaming Sheng; Qiuzhi Gao; Yu Fan; Xiang Xie
Journal:  Biomed Rep       Date:  2020-11-17

2.  A Properly Balanced Reduction Diet and/or Supplementation Solve the Problem with the Deficiency of These Vitamins Soluble in Water in Patients with PCOS.

Authors:  Małgorzata Szczuko; Iwona Szydłowska; Jolanta Nawrocka-Rutkowska
Journal:  Nutrients       Date:  2021-02-26       Impact factor: 5.717

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