Front. Endocrinol. Frontiers in Endocrinology Front. Endocrinol. 1664-2392 Frontiers Media S.A. 10.3389/fendo.2023.1273218 Endocrinology Systematic Review Association between MTHFR gene C677T polymorphism and gestational diabetes mellitus in Chinese population: a meta-analysis Tan Xi Chen Hongqin * Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University) of Ministry of Education, Chengdu, Sichuan, China

Edited by: Pradeep Kumar, Veer Bahadur Singh Purvanchal University, India

Reviewed by: Vandana Rai, Veer Bahadur Singh Purvanchal University, India; Rami M. Elshazli, Horus University, Egypt; Umamaheswaran Gurusamy, Nationwide Children’s Hospital, United States

*Correspondence: Hongqin Chen, chenhongqin2022@163.com

30 10 2023 2023 14 1273218 07 08 2023 13 10 2023 Copyright © 2023 Tan and Chen 2023 Tan and Chen

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 Background and purpose

The relationship of the methylenetetrahydrofolate reductase (MTHFR) gene C677T polymorphism with the incidence of gestational diabetes mellitus (GDM) in the Chinese population remains controversial. This study aimed to further clarify the effect of the MTHFR gene C677T polymorphism on GDM risk among Chinese pregnant women based on current evidence.

 Methods

Several databases were searched up to July 29, 2023 for relevant case-control studies. The numbers of patients with and without the T allele of the MTHFR gene C677T polymorphism in the GDM and control groups were determined, and all statistical analyses were performed by RevMan 5.3 software and STATA 15.0 software. Trial sequential analysis (TSA) was performed by TSA version 0.9 beta software to determine the required information size.

 Results

A total of 17 case-control studies involving 12345 Chinese participants were included. The pooled results demonstrated that the T allele of the MTHFR gene C677T polymorphism was significantly associated with an increased risk of GDM, which was manifested by the five gene models of the MTHFR C677T polymorphism [T vs. C: odds ratio (OR)=1.59, P=0.03; TT vs. CC: OR=2.24, P<0.001; TC vs. CC: OR=1.28, P=0.05; (TT+TC) vs. CC: OR=1.55, P=0.003; TT vs. (TC+CC): OR=1.89, P<0.001]. Subgroup analysis based on the regions indicated that the significant relationship between the T allele of the MTHFR gene C677T polymorphism and an increased risk of GDM was detected only among the southern population [T vs. C: OR=1.62, P=0.09; TT vs. CC: OR=2.22, P=0.004; TC vs. CC: OR=1.17, P=0.28; (TT+TC) vs. CC: OR=1.43, P=0.03; TT vs. (TC+CC): OR=1.97, P=0.006]. TSA plots showed that the information sizes for the association between the MTHFR gene C677T polymorphism and GDM risk were sufficient in the homozygote (TT vs. CC) and recessive (TT vs. TC+CC) models.

 Conclusion

The MTHFR gene C677T polymorphism is closely related to susceptibility to GDM in the southern Chinese population, and the C-T mutation serves as an important genetic risk factor for GDM. More well-designed large case-control studies are needed to further confirm the above findings.

 methylenetetrahydrofolate reductase C677T polymorphism gestational diabetes mellitus China meta-analysis trial sequential analysis section-in-acceptance Diabetes: Molecular Mechanisms Introduction

Gestational diabetes mellitus (GDM) is a common complication during pregnancy, posing significant health risks to both the fetus and the mother. The incidence of GDM has been rising, with reported rates ranging from 1% to 14% internationally and from 2% to 18% in China (1–4). Additionally, the onset of GDM is occurring at increasingly younger ages (2). GDM can have adverse effects on both the mother and the fetus, leading to complications such as miscarriage, preterm birth, diabetic ketoacidosis, infection, postpartum hemorrhage, fetal distress, macrosomia, neonatal respiratory distress syndrome, and neonatal hypoglycemia (5). Furthermore, both pregnant women with GSM and their offspring have an increased risk of developing type 2 diabetes in the long term (5). Therefore, identifying potential and modifiable risk factors for GDM is a valuable strategy to enhance the health status of pregnant women and their offspring.

Homocysteine (Hcy) is a reactive amino acid associated with vascular injury that impacts glucose and lipid metabolism. Previous studies have indicated that Hcy levels are higher in GDM patients than in women with normal pregnancies, suggesting a potential close relationship between Hcy levels and GDM and its complications (6). Relevant studies suggest that insulin resistance is a central factor in the development of GDM, and plasma Hcy levels are positively correlated with fasting insulin levels (7). The insulin resistance index directly influences plasma Hcy levels, although this remains a subject of significant debate (8, 9).

Methylenetetrahydrofolate reductase (MTHFR) can catalyze 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, participating in the remethylation of Hcy and keeping Hcy levels relatively low in the body. Variations in the MTHFR gene can lead to disruptions in multiple physiological and biochemical reactions in the body, such as modifications in the methylation of nucleic acids and proteins and the regulation of the cell cycle. The MTHFR gene is located on the short arm of human chromosome 1 (1p36.3), and polymorphisms in the MTHFR gene can result in reduced enzyme activity, causing folate metabolism disturbances, reduced 5-methyltetrahydrofolate production, impaired DNA methylation, metabolic disruptions of Hcy, and the accumulation of Hcy in the bloodstream. Currently, hundreds of single nucleotide polymorphisms (SNPs) have been identified in the MTHFR gene, with the C677T site being the most closely associated with diseases. When this gene polymorphism occurs, it may lead to reduced or impaired MTHFR enzyme activity, disrupted folate metabolism, and elevated Hcy levels and consequently result in related complications (10–13). Some studies have demonstrated that the MTHFR gene C677T polymorphism is closely related to the risk of diabetes mellitus (DM) (14, 15). Some investigators also revealed that the C-T mutation in the MTHFR C677T gene might lead to increased susceptibility to GDM (16, 17). However, whether the MTHFR gene C677T polymorphism leads to an increased risk of GDM in the Chinese population remains controversial.

Therefore, this meta-analysis aimed to further identify the effect of the MTHFR gene C677T polymorphism on GDM risk among Chinese pregnant women based on current evidence.

 Materials and methods

The current meta-analysis was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses 2020 guidelines (18).

Literature search

In this meta-analysis, the CNKI, VIP, WanFang, Medline, Web of Science and EMBASE databases were searched from inception to July 29, 2023. The following terms were used during the search: single nucleotide polymorphism, SNP, polymorphism, gestational diabetes mellitus, pregnancy-induced diabetes, methylenetetrahydrofolate reductase and MTHFR. The detailed search strategy was as follows: (single nucleotide polymorphism OR SNP OR polymorphism) AND (gestational diabetes mellitus OR pregnancy-induced diabetes) AND (methylenetetrahydrofolate reductase OR MTHFR). Moreover, MeSH terms and free-text words were both applied, and references cited in the included studies were also reviewed.

 Inclusion criteria

Studies that met the following criteria were included: 1) studies of the association between the MTHFR gene C677T polymorphism and the incidence of GDM among pregnant Chinese women; 2) studies in which the numbers of patients with and without the T allele of the MTHFR gene C677T polymorphism in the GDM and control groups were provided for the calculation of odds ratios (ORs) with 95% confidence intervals (CIs); and 3) high-quality studies with a Newcastle-Ottawa Scale (NOS) score of 6 or higher (19).

 Exclusion criteria

Studies that met the following criteria were excluded: 1) letters, editorials, animal trials, reviews or case reports; and 2) studies with duplicated or overlapped data.

 Data collection

The following information was extracted from each included study: the first author, publication year, sample size, number of patients with and without GDM, genotype detection method, number of patients with different genotypes and NOS score.

 Quality assessment

The NOS was applied to assess the methodological quality of the included studies because all included studies were cohort studies. As mentioned above, only studies with an NOS score ≥ 6 were included.

The literature search, literature selection, data extraction and quality assessment were independently conducted by two authors, and all disagreements were resolved by team discussion.

 Statistical analysis

The heterogeneity between studies was assessed by using I2 statistics and the Q test. If significant heterogeneity was detected, defined as I2 > 50% and/or P < 0.1, the random effects model was applied; otherwise, the fixed effects model was applied (20). ORs and 95% CIs were combined to evaluate the effect of this polymorphism on GDM risk under the allele model (T vs. C), homozygote model (TT vs. CC), heterozygote model (TC vs. CC), dominant model (TT+TC vs. CC) and recessive model (TT vs. TC+CC). The overall population was stratified according to region (northern vs. southern), and subgroup analysis was conducted by region. Sensitivity analysis was conducted to determine the sources of heterogeneity and assess the stability of the overall results. In addition, Begg’s funnel plot and Egger’s test were conducted to detect publication bias, and significant publication bias was defined as P < 0.05 (21, 22). If obvious publication bias was detected, then the fill-and-trim method was applied to identify potentially unpublished studies (23). The above analysis was performed by RevMan 5.3 software and STATA 15.0 software.

Trial sequential analysis (TSA) was conducted according to the guidelines of former publications (24, 25). A significance level of 5% for type I error and a significance level of 20% for type II error were set to evaluate the required sample size and TSA monitoring boundaries, which was performed by TSA version 0.9 beta software.

 Results Literature search and selection

The specific literature search and selection process is shown in Figure 1 . Initially, 112 records were identified from the six databases. Ultimately, a total of 18 available studies were included in this meta-analysis after reviewing the titles, abstracts and full texts (14, 26–41).

Prisma flow diagram of this meta-analysis.

 Basic characteristics of the included studies

As shown in Table 1 , 12345 Chinese participants were enrolled, with sample sizes ranging from 60 to 5614, and nine studies were from southern China. Among the enrolled patients, 3439 were diagnosed with GDM. Detailed data are presented in Table 1 . Specific information about the NOS score is shown in Supplementary Table 1 .

Basic characteristics of included studies.

Author Year Region Sample size GDM Non-GDM Genotyping method Allele model Homozygote model Heterozygote model Dominant model Recessive model NOS
T-GDM C-GDM T C TT-GDM CC-GDM TT CC TC-GDM CC-GDM TC CC TT+TC-GDM CC-GDM TT+TC CC TT-GDM TC+CC-GDM TT TC+CC
Cheng (26) 2016 S 214 91 123 QF-PCR 50 132 56 190 10 51 3 70 30 51 50 70 40 51 53 70 10 81 3 120 7
Yang (27) 2016 S 363 166 197 TaqMan 96 234 151 241 16 85 30 75 64 85 91 75 80 85 121 75 16 149 30 166 7
Guan (28) 2018 N 60 27 33 Sequencing 24 30 31 35 6 9 13 15 12 9 5 15 18 9 18 15 6 21 13 20 6
Li (30) 2019 N 490 158 332 Sequencing 81 77 132 200 45 44 54 122 69 44 156 122 114 44 210 122 45 113 54 278 8
Xing (31) 2019 S 490 158 332 Sequencing 159 157 264 400 45 44 54 122 69 44 156 122 114 44 210 122 45 113 54 278 8
Chen (29) 2019 S 314 155 159 Sequencing 11 155 9 159 31 40 20 84 84 40 55 84 115 40 75 84 31 124 20 139 7
Ni (32) 2020 S 199 97 102 FQ-PCR 98 96 65 139 24 23 13 50 50 23 39 50 74 23 52 50 24 73 13 89 7
Liu (14) 2020 N 366 67 299 Microarray – – – – 24 8 92 56 35 8 151 56 59 8 243 56 24 43 92 207 7
Fang (33) 2021 N 1242 568 674 FQ-PCR 330 806 519 829 55 293 103 258 220 293 313 258 275 293 416 258 55 513 103 571 8
Wang (35) 2021 N 250 130 120 FQ-PCR 160 100 64 176 55 25 18 74 50 25 28 74 105 25 46 74 55 75 18 102 7
Niu (34) 2021 N 198 83 115 Sequencing 70 96 65 165 21 34 9 59 28 34 47 59 49 34 56 59 21 62 9 106 7
Zhang (38) 2022 N 200 100 100 Sequencing 97 103 67 133 26 29 12 45 45 29 43 45 71 29 55 45 26 74 12 88 7
Lu (36) 2022 S 1251 345 906 TaqMan – – – – 37 179 86 444 129 179 376 444 166 179 462 444 37 308 86 820 8
Mo (37) 2022 S 180 80 100 FQ-PCR 122 38 77 123 52 10 15 38 18 10 47 38 70 10 62 38 52 28 15 85 7
Gu (39) 2023 S 5614 1054 4560 FQ-PCR – – – – 85 568 369 2415 401 568 1776 2415 486 568 2145 2415 85 969 369 4191 8
Huang (40) 2023 S 822 146 676 Sequencing – – – – 29 76 53 404 41 76 219 404 70 76 272 404 29 117 53 623 8
Liu (41) 2023 N 92 14 78 TaqMan – – – – 7 4 14 31 3 4 33 31 10 4 47 31 7 7 14 64 6

GDM, gestational diabetes mellitus; QF-PCR, quantitative fluorescent polymerase chain reaction; FQ-PCR, fluorescence quantitative polymerase chain reaction; NOS, Newcastle-Ottawa Scale.

 The association between the <italic>MTHFR</italic> gene C677T polymorphism and GDM risk in the Chinese population

The pooled results demonstrated that the MTHFR gene C677T polymorphism was significantly related to the risk of GDM in the allele model (OR=1.59, 95%:1.05-2.41, P=0.03; I2 = 94%, P<0.001) ( Figure 2 ), homozygote model (OR=2.24, 95%:1.44-3.50, P<0.001; I2 = 89%, P<0.001) ( Figure 3 ), heterozygote model (OR=1.28, 95%:0.99-1.65, P=0.05; I2 = 82%, P<0.001) ( Figure 4 ), dominant model (OR=1.55, 95%:1.16-2.06, P=0.003; I2 = 89%, P<0.001) ( Figure 5 ) and recessive model (OR=1.89, 95%:1.32-2.72, P<0.001; I2 = 86%, P<0.001) ( Figure 6 ). Patients with the T variant allele were more likely to develop GDM ( Table 2 ).

The association between MTHFR gene C677T polymorphism and risk of gestational diabetes mellitus in Chinese population under the allele model.

The association between MTHFR gene C677T polymorphism and risk of gestational diabetes mellitus in Chinese population under the homozygote model.

The association between MTHFR gene C677T polymorphism and risk of gestational diabetes mellitus in Chinese population under the heterozygote model.

The association between MTHFR gene C677T polymorphism and risk of gestational diabetes mellitus in Chinese population under the dominant model.

The association between MTHFR gene C677T polymorphism and risk of gestational diabetes mellitus in Chinese population under the recessive model.

Results of meta-analysis.

No. of studies Odds ratio 95% confidence interval P value I2(%) P value
Allele model (T vs C) 12 1.59 1.05-2.41 0.03 94 <0.001
 Region
  North 6 1.57 0.81-3.04 0.19 95 <0.001
  South 6 1.62 0.92-2.85 0.09 91 <0.001
Homozygote model (TT vs CC) 17 2.24 1.44-3.50 <0.001 89 <0.001
 Region
  North 8 2.26 0.96-5.31 0.06 91 <0.001
  South 9 2.22 1.28-3.83 0.004 88 <0.001
Heterozygote model (TC vs CC) 17 1.28 0.99-1.65 0.05 82 <0.001
 Region
  North 8 1.50 0.85-2.65 0.16 86 <0.001
  South 9 1.17 0.88-1.56 0.28 79 <0.001
Dominant model (TT+TC vs CC) 17 1.55 1.16-2.06 0.003 89 <0.001
 Region
  North 8 1.72 0.91-3.27 0.10 91 <0.001
  South 9 1.43 1.03-1.98 0.03 87 <0.001
Recessive model (TT vs TC+CC) 17 1.89 1.32-2.72 <0.001 86 <0.001
 Region
  North 8 1.82 0.97-3.38 0.06 87 <0.001
  South 9 1.97 1.22-3.19 0.006 87 <0.001

However, subgroup analysis stratified by region revealed a significant association between the MTHFR gene C677T polymorphism and an increased risk of GDM only among the southern population in the allele model (OR=1.62, 95%:0.92-2.85, P=0.09; I2 = 91%, P<0.001), homozygote model (OR=2.22, 95%:1.28-3.83 P=0.004; I2 = 88%, P<0.001), heterozygote model (OR=1.17, 95%:0.88-1.56, P=0.28; I2 = 79%, P<0.001), dominant model (OR=1.43, 95%:1.03-1.98, P=0.03; I2 = 87%, P<0.001) and recessive model (OR=1.97, 95%:1.22-3.19, P=0.006; I2 = 87%, P<0.001). Although a significant difference in the allele model and heterozygote model was not shown, an obvious tendency was observed ( Table 2 ). Thus, southern Chinese pregnant women with the T variant allele of the MTHFR gene C677T polymorphism showed significantly increased susceptibility to GDM overall.

 Sensitivity analysis

Sensitivity analysis for the five gene models was performed. Overall, the results in the homozygote model ( Supplementary Figure 1B ), dominant model ( Supplementary Figure 1D ) and recessive model ( Supplementary Figure 1E ) were stable and reliable. However, studies by Mo et al. (37) and Wang et al. (35) showed an impact on the overall results in the allele model ( Supplementary Figure 1A ), and several studies (14, 28–30, 32, 37, 39, 40 31, 35, 38) showed an impact on the overall results in the heterozygote model ( Supplementary Figure 1C ). Thus, more high-quality studies are still needed to further confirm our findings.

 Publication bias

Similarly, publication bias for the five gene models was assessed. According to Begg’s funnel plots ( Supplementary Figures 2A–E ) and Egger’s test P values (allele model: P=0.045; homozygote model: P=0.011; heterozygote model: P=0.037; dominant model: P=0.010; recessive model: P=0.028), significant publication bias was observed. Thus, the fill-and-trim method was applied to identify potentially unpublished studies. According to filled funnel plots, no potentially unpublished publications for the allele model ( Supplementary Figure 3A ) or heterozygote model ( Supplementary Figure 3C ) were found. Three, six and two potentially unpublished studies were detected for the homozygote model ( Supplementary Figure 3B ), dominant model ( Supplementary Figure 3D ) and recessive model ( Supplementary Figure 3E ), respectively. The potentially unpublished studies had no significant effect on the overall results in the homozygote model (filled OR=1.74, 95% CI: 1.12-2.68, P=0.013) and recessive model (filled OR=1.63, 95% CI: 1.13-2.36, P=0.009). However, in the dominant model, a significant effect on the overall results caused by the six potentially unpublished studies was observed (filled OR=1.06, 95% CI: 0.80-1.42, P=0.678). Therefore, to further clarify the association between the MTHFR gene C677T polymorphism and the risk of GDM, more high-quality studies should be performed.

 Trial sequential analysis

Supplementary Figure 4 shows the TSA results. In Supplementary Figures 4B and E , the cumulative Z-curve cut crossed TSA boundaries (red polylines), indicating that the information size was adequate and that the conclusions were robust. However, the Supplementary Figures 4A, C and D show negative results. Therefore, more case-control studies are still needed to further confirm our findings.

 Discussion

The current meta-analysis included 17 relevant studies with 12345 participants and explored the relationship between the MTHFR gene C677T polymorphism and susceptibility to GDM among pregnant Chinese women. Based on currently available evidence, we demonstrated that the T variant allele could serve as a risk factor for GDM among the southern Chinese population. However, due to the limitations in the included studies and our analysis, more randomized controlled trials (RCTs) are needed to further confirm our findings.

It has been reported that the serum Hcy level in GDM patients is significantly higher than that in non-GDM patients (34). Serum Hcy levels have been identified as an independent risk factor for the occurrence of GDM, indicating a strong correlation between elevated Hcy levels and the development of GDM. Hcy can serve as a marker for monitoring the progression of GDM and as a potential predictive factor for evaluating microvascular changes, reflecting the status of blood sugar control (34). A possible reason is that during pregnancy, the maternal body and placenta secrete anti-insulin hormones, leading to increased insulin resistance, which in turn causes elevated Hcy levels. Elevated Hcy levels further inhibit pancreatic β-cell insulin secretion, resulting in an increase in blood glucose levels (42). These two factors have a reciprocal causal relationship and mutually influence each other. Therefore, elevated Hcy levels may serve as a pathological basis for promoting the occurrence and development of GDM (42).

The reduction in enzyme activity caused by the C677T mutation in the MTHFR gene is an important factor leading to elevated Hcy levels (43). MTHFR is a key enzyme involved in Hcy metabolism, catalyzing the conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, which promotes the conversion of Hcy to methionine (14). The C677T mutation site can lead to the substitution of methionine for alanine in MTHFR isoleucine, resulting in decreased MTHFR enzyme activity. This impedes the conversion of Hcy to methionine, leading to the accumulation of Hcy in the body and subsequently causing an increase in the serum Hcy concentration, which contributes to the development of GDM (44). The results from the study by Pawlik A et al. showed that MTHFR CT heterozygous mutations reduced enzyme activity to approximately 75% of the CC type, while TT genotype mutations led to even more significant decreases, reaching approximately 50% or lower (45). The aforementioned reports confirm that different genotypic mutations of MTHFR C677T can cause a reduction in MTHFR enzyme activity, resulting in elevated serum Hcy levels. Therefore, the T variant allele in the MTHFR gene C677T polymorphism leads to an increased risk of GDM.

Most included studies revealed a relationship between the MTHFR gene C677T polymorphism and an increased risk of GDM. However, studies by Fang et al. (33) and Yang et al. (27) reported opposite results, and they suggested several potential causes. Yang et al. did not find a significant correlation between mutations of MTHFR C677T and plasma Hcy levels, suggesting that the T variant allele in the MTHFR gene C677T polymorphism may have a relatively minor impact on Hcy metabolism in pregnant Han Chinese women. However, this mutation may reduce the risk of GDM through the alteration of other metabolic pathways within the body, thereby masking the potential adverse effects of Hcy metabolism changes caused by the C-T mutation in MTHFR C677T (27). In addition, the metabolism of Hcy is regulated by various factors, including genetics and nutrition. The potential influence of confounding factors such as plasma/red blood cell folate levels and the glomerular filtration rate in the study subjects might lead to biases in the research findings (27). Moreover, the sample size with 363 patients in the study by Yang et al. was relatively small, and the test performance of their results was only 0.48.

There are several limitations in our meta-analysis. First, the sample sizes in several included studies were relatively small, which might cause some bias. Second, the genotyping methods in the included studies differed, and the accuracy of different methods may vary. Third, a more detailed subgroup analysis based on other important parameters, such as race and age, could not be performed because the original data were unavailable. Fourth, significant heterogeneity among the included studies was detected.

 Conclusion

The MTHFR gene C677T polymorphism is closely related to susceptibility to GDM in the southern Chinese population, and the C-T mutation serves as an important genetic risk factor for GDM.

 Data availability statement

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.

 Author contributions

XT: Conceptualization, Data curation, Formal Analysis, Methodology, Writing – original draft. HC: Project administration, Supervision, Validation, Writing – review & editing.

 Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by Sichuan Science and Technology Program (2023NSFSC1606) and the National Key Research and Development Program of China (2022YFC2704600, 2022YFC2704604).

 Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

 Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo.2023.1273218/full#supplementary-material

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