Introduction

Recurrent pregnancy loss (RPL) is a spontaneous loss of pregnancy, taking place before 20th weeks of gestation before embryo viability. Most common causes of RPL occur during intrauterine fetus development involving chromosomal abnormalities or an interruption in the fetal–maternal interface, both reasons may lead to loss of pregnancy. There are several risk factors have triggering sudden onset of pregnancy loss. This includes structural uterine anomalies, hormonal disturbances and autoimmune syndromes. However the exact cause of RPL remain unidentified in 50% of affected women [1, 2]. The published percentages for early RPL over the past couple of years is determined and recorded during the usual routine investigations done by females during early pregnancy prenatal visits. However there is a probability of fifty percent loss of pregnancy might occur very early even at preclinical phases. Mainly due to biochemical reasons or unsuccessful implantation processes [3] and around 9 % of officially clinically confirmed pregnancies are lost during first 14 weeks of gestation [4, 5].

The One Carbon Metabolic Pathway (OCMP) malfunction has a significant impact on the rate at which RPL occurs. This topic was highlighted in previously published texts [6, 7]. Genomic polymorphisms may disturb the OCMP pathway, mainly polymorphisms occurring in related thrombophilia genes especially the ones in the Methyletetrahydrofolate gene (MTHFR).Also, OCMP pathway is affected if there is a deficit in folic acid intake as folate is the main substance in this pathway, folate have a great impact on the fetal epigenetic encoding through OCMP [8, 9]. Single nucleotide polymorphisms (SNPs) in Methyltransferase Reductase (MTRR) gene (MTRR A66G) and Methyltransferase (MTR) gene (MTR A2756G) are directly related to decreased level of folate as its also directly with the excessive release for homocysteine among women having RPL [10].

MTRR A66G Snp causes a change in isoleucine to methionine in the codon 22. This transmutation is inserted within disturbing normal function of flavin mononucleotide binding domain [11]. This mutation alters normal MTRaction disturbing translation processes of methylation into methionine causing a rise in homocysteine levels. Homocysteine is an amino acid having a high content of sulpher. It is produced throughout the breakdown of methionine. The key enzymes controlling these processes are MTR, and MTRR. Hyperhomocysteinemia has a great impact on the development of thrombotic state among individuals. Furthermore, various well-known hereditary mutations in enzymatic genes (MTR, and MTRR) are proved to be linked with high blood homocysteine levels causing many maternal co-morbidities and placenta abruptions [12].

As a consequence of raised homocysteine levels there is a reduction in the accessibility of S-adenosylmethionine which leads to DNAhypomethylation and therefore the emerge of neonatal congenital/ neural deficiencies (neural tube defects and spina bifida) among other gestational morbidities [11].

Hyperhomocysteinemia is directly correlated with the presences of hypercoaguable state, as it encourages endothelium cellular malfunction, platelet clotting as well vascular smooth muscle cell propagation in the uteroplacental circulation affecting the normal blood flow in the placental maternal-fetal interface and enhancing the chances for RPL to occur [13, 14]. Remethylation of homocysteine happens through a cobalamin enzyme called methionine synthase [15]. The mentioned folate cycle is regulates homocysteine absorption through methionine synthase enzyme. Flowing folate (5-methyl tetrahydrofolate, 5-MTHF) in the circulation gives methyl groups to methionine synthase enzyme to be used in the intracellular methylation processes. This maternal thrombotic state results in pelvic floor infarctions, huge placenta villous fibrin secretion as well as fetus thrombus vasculopathy are all precise placenta injuries which is directly related to poor fetal outcomes[16].

MTHFR is an important studied genetic marker in comparison to other studied genetic polymorphisms related to RPL [14] [17, 18]. In spite of widespread researches done in prenatal departments and in in-vitro fertilization centers, the early prediction of RPL till now is still difficult to diagnose [19]. Therefore, this research is an effort to explore the relationship of the chosen genetic polymorphisms MTR A2756G and MTRR A66G with RPL.

Subject and methods

Four hundred female formed the case group were enrolled in this research, two hundred women who had gone through two or more successive unexplained RPL before twenty weeks of pregnancy, while control group consisted of two hundred women who had normal uncomplicated pregnancies.

Investigations were done to exclude RPL cases caused by obvious medical causes. RPL cases tested positive for glucose tolerance test, antiphospholipid antibodies, lupus anticoagulants, β‑microglobulin test, and abnormal karyotype. Uterine abnormalities, polycystic ovaries assessed by ultrasonography were excluded from the study. Hysteroscopy was also done to exclude any uterine abnormality, adhesions if present. Hormonal profiling was done for follicle‑stimulating hormone on day 2, luteinizing hormone, prolactin as well as thyroid profile test was checked.

Ethical approval numbered (19266) was obtained from the Medical Research Ethical committee of our institute National Research Center (NRC). This research article was derived from a research funded Project from the National Research Center, Cairo, Egypt. Project Fund number (12060180). Records were collected after obtaining informed written consent from all the participants.

Sample size calculation

Bearing in mind the power of the current research to have Confidence interval (CI) 95%, margin of error 5%, the sample size was calculated grounded on the population size of RPL referred cases to our referral center. The sample size was calculated to be at least 180 for each group (RPL cases and controls).

Genetic analysis

Five ml intravenous blood sample were withdrawn from all subjects. Screening for MTRA2756G and MTRR A66G SNPs was done for both studied groups. The genomic DNAwas extracted from peripheral blood using high Salting out method [20]. Genotyping was accomplished through Folate metabolism kit (DNA Technology) Russia. Steps were done according to the manufacturer's protocol. Totally real-time PCRreactions were done in duplicate in Real- Time PCR(Quant studio 5) USA manufactures. Genotypes of the selected SNPs were identified depending on parallel hybridization of two alternative sequence-specific typing probes labeled with altered fluorophores using melting curve analysis showing different genotypes for example mutant variant as shown in Fig.1 Both alleles (MUTANT and WILD) are shown in Fig 1. The ct (curve thresh-hold) of the MELTING TEMPERATURE of the mutant genotype (red) melting curve appeared at higher melting temperatures (54 °C) and ct of the melting temperature(blue) melting curve of wild type appeared at lower temperature (46 °C) meaning that this patient is carrying the mutant genotype, according to protocol guideline. Around 10% of the entire samples were re‑genotyped (haphazardly chosen), for quality monitoring and no difference genotypes results was recorded.

Fig. 1
figure 1

Melting curve plot for mutant genotype for SNPs in MTR and MTRR

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Statistical analysis

Hardy‑Weinberg equilibrium evaluates was done to record the observed and expected genotype incidences by Chi‑square test. Chi‑square test was used to calculate frequencies of different genotypes among both studied groups. Calculation for Odds ratios (ORs) was done results is presented in the 95% confidence intervals (95% CIs). SPSS (IBM SPSS Statistics, Version 22) was used for statistical inquiry.

Results

Demographic features for study participants

Demographic features of case group and control involved in this research are presented in Table 1. Both groups are corresponding in age showing no statically significance (26 ± 2.9 vs. 26 ± 3.5); p = 0.9. Regarding body mass index (BMI) and consanguinity, no statistical significance noticed in both groups, we recorded mean of BMI (25 ± 2.5 vs. 25.3 ± 2.9); p = 0.27 and positive consanguinity (15% vs. 11.5 %); p = 0.3 respectively. There was no difference in consanguinity rate between the case and control group, so it is not considered as an added risk factor to increase susceptibility for RPL in our study population.

Table 1 Characteristics of both studied groups
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Distribution of genetic polymorphisms among RPL cases and controls

Frequencies of MTR A2756G and MTRR A66G SNPs were analyzed in both studied groups. Regarding MTR A756G Snp statistical analysis showed that MTR A2756G Snp was not directly correlated with an increased risk for RPL as (AG vs.GG) had an odds ratio (O.R) and confidence interval (C.I) of (1.36(0.90–2.07)), P = 0.1 and (GG vs. AA) had OR; CI = (1.13(0.56–2.29)), P = 0.7. Even dominate and recessive model showed no statistical significance having p = 0.1 and 1.0 respectively. Mutant G allele frequency in the cases group compared to control group was (27.75% vs. 23.25%) respectively in the MTR gene but this increase of mutant allele did not reach statistical significance (P > 0.05) as shown in Table 2 and 3. As for MTRR A66G the frequency of mutant homozygous genotype (GG) was statistically significant among RPL group in comparison to control group having O.R; (C.I) = 1.22(1.12–2.23), P = 0.012. While the incidence of G allele was statistically higher in control group in comparison to RPL group having O.R and C.I of 1.99(1.48–2.67), p = 0.00 as shown in Table 2 and 3. MTR A2756G and MTRR A66G SNPs were consistent with Hardy‑Weinberg (HW) equilibrium regarding both studied groups; P ≥ 0.05 as shown in Table 3. Genotypes and allele frequencies for MTR A2756G and MTRR A66G SNPs are demonstrated in Fig. 2 and Fig. 3.

Table 2 Frequency distribution of different genotypes in MTRR and MTR SNPs
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Table 3 Statistical significance of different genotypes in MTRR and MTR SNPs
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Fig. 2
figure 2

Genotype and allele distribution of different genotypes in MTR

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Fig. 3
figure 3

Genotype and allele distribution of different genotypes in MTRR

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Association of MTR A2756G, MTRR A66G and with recurrent pregnancy loss

The (O.R) analysis with respect to MTRR A2756G showed that women carrying GG genotypes presented a noteworthy augmented risk of 1.2 folds for RPL in comparison to women carrying AA genotype.

Discussion

Decades were spent in exploring causes or risk factors leading do pregnancy loss. RPL in specific remains an important challenging health issue as its etiology is still uncertain. In the current research, the influence of MTRA2756G and MTRR A66G on RPL is evaluated. It was important to explore the polymorphism of the MTRamong RPL cases as it was proven that MTRA2756G gene might cause escalation in blood homocysteine levels [21]. MTRA2756G is a parental risk, it was acknowledged to be associated with high incidences of RPL, Down syndrome, small for gestational age [22] other health issues for example; breast cancer. Some researches had identified the link of MTRA2756G SNPwith high rate of RPL incidences [14, 23, 24].

However in our research, both AG and GG genotypes in MTR A2756G SNP were not correlated to RPL. Ticconi and his colleagues gave similar results which agreed with our study [17]. The variability in different results regarding SNP frequencies among different researches is mainly due to the variability in the presence of the MTR A2756G polymorphism among diverse geographical areas [25, 26].

Huang and his collegues stated that mutant allele as well as homozygous genotype of MTR A2756G was not common among RPL women which and that MTRR A66G polymorphism showed no significant difference between cases and controls (p > 0.05). which was in contrast to our findings because MTRR in our study was highly signifcant [14]. Two hundred RPL women and 258 controls were included in a study done in north India. The study reported that MTR A2756G is not directly correlated with the risk of having RPL which was in an agreement with our results.

Regarding MTRR A66G Snp in our research the distribution of homozygous mutant variant GG was found to be the higher among RPL women in comparison to controls. Regarding the distribution of MTRR G allele (Mutant allele) was 33.7% among RPL group and 28.2% among control group. Our research revealed a direct relationship of mutant variant GG with risk of having RPL. There is a risk of 1.2 folds of having RPL regarding women carrying GG genotype compared to their controls. This result is also similar to findings documented in other studies [1, 27,28,29]. However other study disagreed with our finding, it documented that the ancestral allele (wild type) of MTRR A66G was triggering risk of more than two folds among RPL women [30]. In a retrospective case–control study; MTRR heterozygous AG genotype was associated with 1.6 fold risk for RPL occurrence having O.R. = 1.62 and 95% C.I = 1.20–2.19, p = 0.002 among Chinese Women [31].

Udumudi (2022) done a study evaluated the relationship of different genotypes in ten clotting genes involved in the coagulatory path mainly; (F2, F5, F13, MTR, MTRR, MTHFR, ANXA5, PROZ, SERPINE1 and VEGFA). Women in the case group were dividing into three groups (women with early recurrent pregnancy loss, pregnancy complications and recurring implantation miscarriage). Genotype frequencies where compared to healthy fertile women in the control group. Results highlighted a statistically significant presence of homozygous mutant genotypes in thrombophilia genes (MTRR, MTR) and their likelihood in causing RPL among Indian women [32]. Also in different ethnic group, a study involved two hundred and six Russian women having RPL and two hundred healthy fertile women in the control group. Authors studied the distribution frequencies of A66G snp in MTRR gene. Results verified that mutant allele in the A66G MTRR gene among RPL women was significantly more common in comparison to women in the control group 22.8% vs. 6.0%. Authors also made a three-locus model of the synergetic act of allelic variants among investigated genes [33]. In a Korean case–control study, one hundred and eighteen women having RPL and two hundred and twenty five women as controls. MTRR A66G snp was investigated and the study proved that MTRR A66G snp is a risk factor RPL. Authors also documented that MTRR A66G polymorphism is associated with increased plasma homocysteine levels (p = 0.019) [34]. A retrospective research targeted to study the frequency of A66G MTRR among pregnant females and if the polymorphism has an impact on folate blood levels. AA and AG genotypes of MTRR A66G was statistically significant among RPL women in comparison to the controls having O.R = 1.89, C.I = 1.61–2.22, P < 0.001. The study recorded that the presence of the A66G MTRR Snp was dramatically associated with disturbed blood folate levels, the authors considered A66G MTRR as an dependent risk feature affecting folate blood levels [35].

Conclusion

MTRR A66G SNP is highly prevalent among women suffering from RPL in comparison to healthy fertile controls, increasing the liability for RPL among Egyptian females. Still, bigger sampling size researches covering all Egyptian governesses are necessary to have a full view of the clinical implication of the selected genetic markers on RPL.