Introduction

Preterm birth (childbirth before 37 weeks of pregnancy, PTB) and low birth weight (birth weight less than 2500 g, LBW) are the two most common adverse birth outcomes [1, 2]. Beck et al. estimated that in 2005, approximately 13.0 million infants were preterm all over the world, representing 9.6% of all births [3]. A report of worldwide child deaths showed that from 2000 to 2013, a global total of 965,000 deaths during the neonatal period could be attributed to direct complications from preterm birth [4, 5]. According to the World Health Organization (WHO) report on LBW, there were over 20 million infants born with LBW, accounting for about 15.5% of total births globally [6]. A prospective community-based study conducted in Nigeria revealed that 55.9% neonatal deaths occurred among LBW infants [7]. Besides the elevated neonatal mortality, PTB and LBW can also result in delayed effects into adolescence and adulthood such as metabolic and chronic diseases (e.g. the metabolic syndrome, diabetes, obesity, and coronary heart disease) [8].

To date, it has been identified that various factors can influence PTB or LBW, including maternal education level, gestational age, gestational hypertension, gestational diabetes mellitus, alcohol consumption, and active or passive smoking status [9–11]. In recent years, quite a number of studies have been conducted on the associations between genetic factors and PTB or LBW. Among numerous genetic variants, the single nucleotide polymorphisms (SNPs) of methylenetetrahydrofolate reductase (MTHFR) gene have become a research hotspot because of its implication in hyperhomocysteinemia, which may lead to an increased risk of adverse birth outcomes [12].

MTHFR, for its function of catalyzing the conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, plays a key role in the important enzymatic process in remethylation of homocysteine (Hcy) into methionine [12, 13]. The MTHFR gene is composed of 11 exons and located on the short arm of chromosome1 (1p36.3) [14]. A cytosine to thymine substitution at position 677 in exon 4 (MTHFR C677T) is a quite common polymorphism in this gene, leading to the substitution of valine for alanine in the corresponding protein and then followed by a reduction in enzyme activity [13]. Consequently, the conversion of Hcy into methionine may be reduced, resulting in accumulation of plasma Hcy [12].

Plenty of studies concerning a potential role of the MTHFR C677T in PTB and LBW susceptibility have been conducted by researchers but with inconsistent results, which might be mainly caused by insufficient population size of one single study [15]. Therefore, it is essential to perform a comprehensive meta-analysis to explore the relationship between polymorphism of MTHFR C677T and PTB as well as LBW susceptibility since some true associations might not be found in small-scale researches. In 2009, a meta-analysis using seven case–control studies showed a significant association of MTHFR mutation with intrauterine growth restriction (IUGR, one of LBW-related outcomes) and the pooled OR was 1.35 (95% CI 1.04–1.75) [16]. A meta-analysis adopting studies published before August 2014 found that there was no association of MTHFR C677T polymorphism with PTB [17]. However, neither of the two meta-analyses differentiated the maternal and neonatal gene sources, nor did they conduct subgroup analysis by gene sources, which might obscure the inherent association. Additionally, several new eligible studies have been published following these two meta-analyses.

With a more rigorous and precise inclusion criteria, we designed a meta-analysis on the association of maternal and neonatal MTHFR C677T with risk of PTB and LBW, respectively. It is worth noting that, in the view of most obstetric and neonatal physicians, small for gestational age (SGA), fetal growth retardation (FGR), and intrauterine growth restriction (IUGR) are generally deemed to manifest as LBW clinically [18]. SGA is defined as a specified birth weight less than the 10th percentile of infants born at a given gestational age. The definitions of FGR and IUGR are similar, usually defined as estimated fetal weight less than the 10th percentile, according to gestational age [19]. Thus, considering the highly similar diagnostic criteria and clinical feature, SGA, FGR, and IUGR were all included as LBW uniformly in this research.

Materials and methods

Search strategy

This meta-analysis was performed following the MOOSE guidelines [20]. A comprehensive review of studies from Embase, Medline, China Biological Medicine Database (CBM), Chinese National Knowledge Infrastructure (CNKI) and Wanfang Database was performed to identify the relevant studies before June 2016. The search was limited to English and Chinese, using the following key words: (“Methylenetetrahydrofolate reductase” OR “MTHFR” OR “C677T” OR “rs1801133”) AND (“variation” OR “polymorphism” OR “mutations”) AND (“Preterm Birth” OR “Low Birth Weight” OR “Intrauterine Growth Retardation” OR “Fetal Growth Retardation” OR “Small for Gestational Age”). References listed in the retrieved articles were also checked and included as additional studies if deemed eligible. For studies using overlapping data or on the same study group, only the most complete or recent studies were included.

Eligibility criteria

Studies included in this meta-analysis should be consistent with the following criteria: (1) studies with case–control design; (2) focusing on the association between MTHFR C677T polymorphism and PTB, LBW, SGA, IUGR, or FGR; (3) providing sufficient information on the numbers or genotype frequencies in cases and controls in each original study; (4) using healthy individuals as controls.

The exclusion criteria were as follows: (1) abstracts, reviews, comments, or case reports; (2) duplicate publications of data from the same study. Studies with the definition or raw data of interest could not be obtained after attempting to contact the corresponding authors via e-mail.

Data extraction and quality assessment

Two investigators extracted the relevant data independently and disagreements were resolved by the third investigator. The following information was extracted: the author’s name, year of publication, country of origin, ethnicity, source of controls, subjects of study, gene sources, obstetric outcomes, diagnostic criteria of cases, genotyping method, and the number of cases and controls for each genotype. In addition, deviation from Hardy–Weinberg equilibrium (HWE) for distribution of the allele frequencies was analyzed by a Chi square test among the controls [21].

The quality of eligible studies was independently assessed by two investigators according to the 9-star Newcastle–Ottawa Scale [22] and the overall scores were obtained for each study. The study with best quality can be assigned nine stars and a study is considered high quality if it scored six stars or more [23].

Statistical analysis

The strength of association between the MTHFR C677T polymorphisms and PTB and LBW risk was estimated by ORs with 95% CIs according to allele contrast (T vs. C), homozygote (TT vs. CC), heterozygote (CT vs. CC), recessive (TT vs. CT + CC), and dominant (TT + CT vs. CC) models. Higgins I 2 statistics were performed to describe the percentage of total variation because of between-study heterogeneity rather than chance [24]. Heterogeneity between studies was deemed statistically significant if I 2 > 50% and then the random effects model (DerSimonian–Laird approach) [25] was performed to pool the effect estimates. Otherwise, a fixed effects model (Mantel–Haenszel approach) [26] was adopted. To detect the sources of heterogeneity, subgroup analysis were conducted by source of controls (hospital- or population-based controls), ethnicity (Asian, Caucasian, or others), country status (developing or developed countries), singleton pregnancy (yes or not), and case definition. To assess the impact of studies with samples not in HWE (P < 0.05), sensitivity analysis was performed by removing these studies and then recalculating ORs with CIs [27]. Publication bias was evaluated with the Egger’s regression asymmetry test, AS-Thompson test, and trim-and-fill method. AS-Thompson test, using an arcsine transformation, has been shown to work reasonably well in studies with substantial heterogeneity [28]. The pooled effect estimates might be inflated if publication bias exists, and trim-and-fill method is usually used to adjust for publication bias [29]. This method incorporates the hypothetical “missing” studies, as though they actually existed, to recalculate a pooled effect estimate [30]. All statistical analyses were carried out using STATA (version 13.0, Stata Corporation, College Station, Texas, USA) and R (version 3.3.0, The R Project for Statistical Computing, Vienna, Austria), by two-sided P values. A P value of <0.05 was considered statistically significant.

Results

Study characteristics

The initial literature search obtained 405 records from Embase, Medline, CBM, CNKI, and Wanfang Databases and eight additional studies identified through other sources. 393 articles were excluded, and a total of 25 studies from 20 articles were included in this meta-analysis (Fig. 1). Moreover, all of the included articles were assigned 6 stars or more. Characteristics of these studies were summarized in Table 1.

Fig. 1
figure 1

Flow diagram of study selection

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Table 1 Main characteristics of studies included in this meta-analysis
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Maternal MTHFR C677T polymorphism and PTB

There were eight studies [31–38] concerning maternal MTHFR C677T gene polymorphism and PTB in this meta-analysis (main results are presented in Table 2). Due to the existence of relatively large heterogeneity between studies (ranging from 65.9 to 81.4%), a random effects model was applied under all the five genetic inheritance models. An increased risk of PTB was indicated under allele contrast model (T vs. C, OR = 1.36, 95% CI 1.02–1.81), homozygote model (TT vs. CC, OR = 1.70, 95% CI 1.07–2.68, Fig. 2), and recessive model (TT vs. CT + CC, OR = 1.49, 95% CI 1.00–2.22), but not dominant model (TT + CT vs. CC) or heterozygote model (CT vs. CC).

Fig. 2
figure 2

Results of the random effect meta-analysis of maternal MTHFR C677T polymorphism and PTB under homozygote model (TT vs. CC)

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Table 2 Main results of the pooled ORs in meta-analysis of the maternal MTHFR C667T polymorphism with PTB and LBW outcomes
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In hospital-based (HB) subgroup, an increased risk of PTB was observed under four genetic inheritance models (for allele contrast model: OR = 1.46, 95% CI 1.08–1.98; for homozygote model: OR = 1.90, 95% CI 1.17–3.08; for recessive model: OR = 1.62, 95% CI 1.05–2.48; for dominant model: OR = 1.55, 95% CI 1.07–2.25; for heterozygote model: OR = 1.40, 95% CI 0.98–2.01). No significant association was found under all the models among population-based (PB) subgroup.

In the subgroup analysis by ethnicity, an increased risk of PTB was observed among Asians under the allele contrast model (OR = 1.48, 95% CI 1.02–2.15) and homozygote model (OR = 1.81, 95% CI 1.03–3.19). No significant association was found under other models of Asian and other ethnicity subgroups.

Pooled results of studies from developing countries indicated that except the heterozygote model, there were significant associations between maternal MTHFR C677T polymorphism and PTB risk under the other genetic inheritance models of allele contrast model (OR = 1.50, 95% CI 1.09–2.07), homozygote model (OR = 1.94, 95% CI 1.17–3.22, Fig. 3), recessive model (OR = 1.64, 95% CI 1.05–2.57), and dominant model (OR = 1.60, 95% CI 1.07–2.39). No significant association was detected in studies from developed countries (Table 3).

Fig. 3
figure 3

Subgroup analysis of maternal MTHFR C677T polymorphism and PTB under homozygote model (TT vs. CC)

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Table 3 Results of subgroup analysis of the maternal MTHFR C667T polymorphism with PTB
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Maternal MTHFR C677T polymorphism and LBW risk

There were 11 studies [31, 34, 39–47] concerning maternal MTHFR C677T gene polymorphism and LBW in this meta-analysis (Table 2). Due to the existence of relatively large heterogeneity between studies (ranging from 54.6 to 80.0%), a random effects model was applied under all the genetic inheritance models except for the recessive model (I 2 = 35.0%). An increased risk of LBW was indicated under allele contrast model (OR = 1.69, 95% CI 1.25–2.28), homozygote model (OR = 2.26, 95% CI 1.44–3.54, Fig. 4), dominant model (OR = 1.71, 95% CI 1.19–2.47), and recessive model (OR = 1.79, 95% CI 1.42–2.26), but not heterozygote model.

Fig. 4
figure 4

Results of the random effect meta-analysis of maternal MTHFR C677T polymorphism and LBW under homozygote model (TT vs. CC)

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In HB subgroup, an increased risk of LBW was observed under all the five genetic inheritance models (for allele contrast model: OR = 1.83, 95% CI 1.31–2.55; for homozygote model: OR = 2.58, 95% CI 1.62–4.09; for recessive model: OR = 1.94, 95% CI 1.51–2.49; for dominant model: OR = 1.89, 95% CI 1.25–2.87; for heterozygote model: OR = 1.52, 95% CI 1.01–2.30), but not among PB subgroup.

In the subgroup analysis by ethnicity, an increased risk of LBW was observed among Asians and Caucasians under all the genetic inheritance models (In Asians, for allele contrast model: OR = 1.93, 95% CI 1.42–2.62; for homozygote model: OR = 3.00, 95% CI 2.02–4.46; for recessive model: OR = 2.18, 95% CI 1.58–3.02; for dominant model: OR = 2.10, 95% CI 1.36–3.25; for heterozygote model: OR = 1.77, 95% CI 1.10–2.85. In Caucasians, for allele contrast model: OR = 2.64, 95% CI 1.82–3.83; for homozygote model: OR = 3.76, 95% CI 1.77–8.01; for recessive model: OR = 3.72, 95% CI 1.77–7.82; for dominant model: OR = 2.83, 95% CI 1.75–4.60; for heterozygote model: OR = 2.45, 95% CI 1.31–4.55). No significant association was found under all the models of other ethnicity subgroups.

Pooled results from developing countries also indicated that there were significant associations between maternal MTHFR C677T polymorphism and LBW risk under all genetic inheritance models (for allele contrast model: OR = 1.92, 95% CI 1.53–2.42; for homozygote model: OR = 3.09, 95% CI 2.09–4.58, Fig. 5; for recessive model: OR = 2.23, 95% CI 1.62–3.08; for dominant model: OR = 2.16, 95% CI 1.55–3.01; for heterozygote model: OR = 1.88, 95% CI 1.30–2.73). However, no such association was detected in studies from developed countries under all these models except for the recessive model (OR = 1.40, 95% CI 1.00–1.96).

Fig. 5
figure 5

Subgroup analysis of maternal MTHFR C677T polymorphism and LBW under homozygote model (TT vs. CC)

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We also conducted subgroup analysis by case definition, and we found an increased risk of LBW under allele contrast model (OR = 4.21, 95% CI 2.15–8.25), homozygote model (OR = 4.21, 95% CI 1.63–10.90), recessive model (OR = 4.21, 95% CI 1.63–10.90), and dominant model (OR = 4.21, 95% CI 1.63–10.90) in subgroup of birthweight less than 5 percentile. Additionally, we found an increased risk of LBW under allele contrast model (OR = 1.51, 95% CI 1.02–2.24) and recessive model (OR = 1.04, 95% CI 1.04–1.99) in subgroup of birthweight less than 10 percentile. Besides, we found significant association between MTHFR C677T polymorphism and LBW risk under allele contrast model (OR = 1.62, 95% CI 1.30–2.01), homozygote model (OR = 2.77, 95% CI 1.76–4.36), recessive model (OR = 2.05, 95% CI 1.43–2.93), and borderline significant association under dominant model (OR = 1.60, 95% CI 1.00–2.57) when birthweight was less than 2500 g (results of subgroup analysis are presented in Table 4).

Table 4 Results of subgroup analysis of the maternal MTHFR C667T polymorphism with LBW
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Neonatal MTHFR C677T polymorphism and PTB or LBW

There were three studies concerning maternal MTHFR C677T gene polymorphism with PTB [31, 48, 49] and LBW [31, 41, 50], respectively, in this meta-analysis. Large heterogeneity between studies (ranging from 58.0 to 86.7%) was detected and a random effects model was applied under all the genetic inheritance models except for the heterozygote model of LBW (I 2 = 0.0%). There was null association between neonatal MTHFR C677T polymorphism and PTB or LBW risk (main results are presented in Table 5). Due to that the total numbers of studies on PTB and LBW were only three, subgroup analysis was not conducted.

Table 5 Main results of the pooled ORs in meta-analysis of the neonatal C667T polymorphism with PTB and LBW
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Sensitivity analysis

Three out of 8 studies of MTHFR polymorphism with PTB risk [31, 34, 35] and 4 out of 11 studies of MTHFR polymorphism with LBW risk [34, 39, 42, 45] were not consistent with HWE. However, the recalculated results were unchanged after excluding these studies (Table 2). The sensitivity analysis showed that the pooled results from this meta-analysis were statistically robust.

All of the six studies on neonatal MTHFR C677T polymorphism and PTB and LBW risk were consistent with HWE, so we did not perform sensitivity analysis.

Publication bias

The P value of Egger’s regression asymmetry test and AS-Thompson test indicated that there was evidence of publication bias in the allele contrast model (Egger’s test, P = 0.048), dominant model (Egger’s test, P = 0.013 and AS-Thompson test, P = 0.018), and heterozygote model (for Egger’s test, P = 0.026 and for AS-Thompson test, P = 0.020) of maternal MTHFR C677T gene polymorphism and LBW. By using trim-and-fill method, the adjusted effect estimates were attenuated, but their statistical significance was consistent with the unadjusted result (for allele contrast model, OR = 1.38, 95% CI 1.03–1.85; for dominant model, OR = 1.54, 95% CI 1.09–2.18; for heterozygote model, OR = 1.22, 95% CI 0.87–1.72). In addition, the results also suggested that in the three models, there were three, two, and two more hypothetical missing studies, respectively. No evidence of publication bias was found in other genetic inheritance models.

Discussion

In the present meta-analysis, 25 studies were included to explore the association between MTHFR gene polymorphisms and the risk of PTB (8 studies for maternal and 3 studies for neonatal C677T mutation) and LBW (11 studies for maternal and 3 studies for neonatal C677T mutation). According to the pooled results, our study showed associations between maternal MTHFR C677T polymorphism with PTB and LBW under most of the genetic models, respectively. Specifically, the carriers of the TT genotype increased the risk of PTB and LBW. In addition, no association between neonatal MTHFR C677T polymorphism with PTB or LBW was detected under all genetic models.

Healthy pregnancy outcome depends not only on trophoblast invasion into the uterine vasculature, but also on the development and maintenance of an adequate uteroplacental circulation in the mother [43]. The placenta, transferring oxygen and nutrients required for fetal development and energy production from maternal blood to the fetus, also has the coagulation/anticoagulation system in balance to fulfill its regular functions [51]. MTHFR plays a key role in folate metabolism, converting 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate, the main form of circulatory folate and the methyl donor for the conversion of homocysteine to methionine [52]. That is to say, MTHFR uses folate to metabolise and thereby remove homocysteine [53]. An increase of plasma Hcy concentration happens when enzyme activity is reduced due to MTHFR C677T, which leads to oxidative stress, arteriolar constriction, endothelial damage, and placental thrombosis [12, 39]. All these conditions might be associated with impaired flow and prothrombotic changes in the vessel wall, inadequate trophoblast invasion into the uterine vasculature, and placental hypoperfusion that subsequently triggers poor pregnancy outcomes including PTB and LBW [33, 43].

Other than PB subgroup, a significant increased risk of PTB and LBW was observed under almost all of the genetic inheritance models in HB subgroup. Although the population-based controls could represent general population well, these results should be interpreted with caution. For the reason that there was only one study included in PB subgroup, the results may be unstable and lack of representativeness. In addition, compared to the corresponding results of HB subgroup, effect sizes of this population-based study were relatively smaller under all of the genetic inheritance models, which indicated an attenuated effect. It is worth noting that this study enrolled both black and Caucasian populations [34]. In another study enrolling black and Caucasian populations as the majority, a quite large increment of effect size was found after including ethnicity as an adjusted factor [41]. For instance, ORs were 0.93 (95% CI 0.64–1.09) and 1.15 (95% CI 0.72–1.85) before being adjusted, while ORs were 0.98 (95% CI 0.69–1.40) and 1.55 (95% CI 0.83–2.90) after being adjusted under heterozygote and homozygote model, respectively [41]. Thus, the ethnicity of subjects may confound the results above and similarly, the attenuated effect of PB subgroup in this meta-analysis may also be confounded by this underlying factor.

Subgroup analysis by ethnicity revealed that Asian carriers of the TT genotype of maternal MTHFR C677T polymorphism were associated with an increased risk of PTB. Unexpectedly, both Asian and Caucasian carriers of the TT genotype of MTHFR C677T polymorphism were associated with an increased risk of LBW. It is possible that diverse genetic backgrounds might interpret these differences [54]. For the reason that only one study was included in Caucasian subgroup when studying the association between PTB and maternal MTHFR C677T polymorphism, the nonsignificant results among Caucasians need further validation in large well-designed studies.

Based on development status, 187 countries of the world were classified into categories of 50 developed countries and 137 developing countries by the GBD 2013 group [55]. Interestingly, compared with pooled results of studies from developed countries, results of developing countries showed statistically significant association between maternal MTHFR C677T polymorphism and PTB as well as LBW risk. In 1996, legislation was permitted or mandated on folic acid fortification in the United States, Canada, and some other developed countries [53]. However, no such fortification has been instituted in developing countries such as China [56]. What is worse, a national survey in China revealed that only 12.1% women of childbearing age took folic acid supplements and only 8.7% of them took folic acid daily before or during early pregnancy [57]. In addition, due to the low income, inadequate prenatal care, and limited food sources, pregnant women in developing countries might not intake folate as adequately as their counterparts in developed countries do [58]. Furthermore, studies have confirmed that women with the MTHFR 677 TT genotype are predisposed to increased plasma homocysteine levels when folate intake is inadequate [59]. From the above, maternal carriers of the TT genotype in developing countries are more likely to deliver infants with PTB or LBW. It is also worth noting that an unexpectedly elevated risk of LBW in developed countries was observed under recessive model (TT vs. CT + CC). An interventional study confirmed that after experiencing a throughout repletion with the 1998 folate U.S. Recommended Dietary Allowance (400 μg/d as dietary folate equivalents) for 7 weeks, women with TT genotype had significant lower serum folate and significant higher plasma total homocysteine (tHcy) concentration than those with CC genotype [60]. However, CT heterozygotes did not differ in their response compared to the CC genotypes [60]. The authors of that study also concluded that the genotype response on 400 μg/d as dietary folate equivalents followed a hierarchical pattern (TT < CT < CC for serum folate and TT > CT > CC for plasma tHcy concentration) [60]. To sum up, it was the hierarchical genotype response pattern for serum folate and plasma tHcy concentration that resulted in the elevated risk of LBW in developed countries in women under recessive model.

As SGA, IUGR, and FGR were all included as LBW in this meta-analysis, subgroup analysis was used to detect the influence of different categories of cases on the final pooled results. Considering that the definitions of cases vary among different studies, we conducted subgroup analysis by the concrete case definition rather than case categories. The results also indicated that maternal carriers of the TT genotype significantly increased the risk of LBW when case definitions were birthweight of less than 5th or 10th percentile, or 2500 g. In the subgroup of birthweight less than 3rd percentile, no significant association was observed. There was only one study included in these subgroups, so the results may be unstable and may lack representativeness.

In the present meta-analysis, all of the sensitivity analysis yielded similar results after excluding studies deviated from HWE, indicating that our results were statistically robust and reliable. Although publication biases were found in several genetic inheritance models, the results of the trim-and-fill method revealed that the publication biases may not affect the stability of our pooled results, strengthening this conclusion.

This meta-analysis had several strengths. Compared with the previous two meta-analyses, more newly published studies were included with a more rigorous and precise inclusion criteria. This is the first meta-analysis, to the best of our knowledge, evaluating the association of maternal and neonatal MTHFR C677T and PTB as well as LBW risk, respectively. By differentiating the maternal and neonatal gene sources in this meta-analysis, we have detected the inherent association between MTHFR C677T and outcomes of interest. We are also the first one, basing on a relatively large sample size, to report that the maternal carriers of the TT genotype in developing countries are susceptible to delivering infants with PTB or LBW.

Some potential limitations of our meta-analysis should be addressed: first, pooled results were based on unadjusted data from the original studies, and a more precise evaluation should be performed by adjusting some potential confoundings such as social-demographic, gestational, and other factors. Second, this meta-analysis was based on single-factor estimates, and was unable to analyze the potential interactions of gene–gene and gene-environment. Last, but not the least, this meta-analysis on neonatal MTHFR C677T polymorphism and PTB and LBW risk was based on a small sample size, indicating that power to detect the reliable association is limited and a possibility of type II error cannot be overlooked. Another consequence of the small sample size mentioned above was that only one study was included in several subgroups, and thus the significance or non-significance of association may be unstable and needs further validation in large well-designed studies.

In summary, the present meta-analysis confirms that there is a conclusive association between maternal MTHFR C677T polymorphism and PTB as well as LBW risk and indicates null significant association between neonatal MTHFR C677T polymorphism with PTB or LBW. This result, however, made an implication that identification of maternal MTHFR C677T mutation in developing countries may play a key role for primary prevention of PTB and LBW and screening pregnant women of high-risk. Further large, well-designed studies are warranted to fully validate association.