Distribution of Methionine Synthase Reductase (MTRR) Gene A66G Polymorphism in Indian Population

Abstract

Methionine synthase reductase (MTRR) is an important enzyme of the folate/homocysteine pathway. It is responsible for regulation of methionine enzyme by reductive methylation. A common variant A66G is reported in the FMN-binding domain of the MTRR gene, which leads to substitution of isoleucine by methionine (I22M) in MTRR enzyme with reduced activity. Reduced catalytic activity of enzyme leads to high homocysteine concentration in blood and increases risk for numerous diseases. The frequency of A66G polymorphism varies in different ethnic groups. The present study has been designed to evaluate the frequency of MTRR A66G gene polymorphism in the Eastern UP population by PCR–RFLP method. Along with this we also performed a meta-analysis to evaluate the global prevalence of this polymorphism. Databases were screened to identified the eligible studies. The prevalence of the G allele and GG genotype was determined by the use of prevalence proportion with 95% CI. Open meta-analyst software was used for the meta-analysis. Total 1000 blood samples were analyzed, the frequencies of A and G alleles were 0.35 and 0.65 respectively. Meta-analysis results revealed that the prevalence of G allele and GG genotype were 49.4% (95% CI 40.6–58.1, p ≤ 0.001) and 24.3% (95% CI 17.8–30.9, p ≤ 0.001) respectively. In sub-group meta-analysis, the lowest frequency of G allele was found in South America (32.7%; 95% CI 14.1–51.3, p ≤ 0.001), and highest in Asia (56.4%; 95% CI 39.5–73.3, p ≤ 0.001). The results of the meta-analysis showed that the Asian population has the highest frequency of G allele and highest frequency of the GG genotype was found in the European population.

Introduction

Folate has important role in pregnancy and cell replication, because it is essentially required for DNA methylation, synthesis and repair. Chronic folate deficiency in vivo and in vitro has been associated with abnormal DNA methylation [1–3], DNA strand breaks [4], altered chromosomal recombination [5] and aberrant chromosome segregation [6]. The exact mechanisms by which these anomalies are related with the folate pathway are not fully elucidated but it is believed that the insufficient methylation of crucial metabolites or direct toxicity of homocysteine play some role in these abnormalities [7]. Folic acid pathway is governed by the dietary/environment and genetic factors and the genetic polymorphisms of the pathway genes regulated the folic acid pathway. Methionine synthase reductase (MTRR) is one of the crucial enzymes of folic acid pathway.

MTRR gene is mapped on chromosome 5p15.2–15.3 and has 15 exons [8]. MTRR is an electron transferase enzyme of FNR (ferredoxin-NADP(+) reductase) family. It is involved in the remethylation of homocysteine by reductive methylation of cob(II)alamin, which, in its unmethylated state, inactivates methionine synthase. The central role of MTRR is maintenance of the function of methionine synthase (MS) by restoration of MS activity [8].

Wilson et al. [9] reported A to G substitution in MTRR gene at 66th nucleotide (MTRRA66G), changes isoleucine into methionine residue (I22M) in enzyme. I22M substitution is located within the flavin mononucleotide-binding domain of the enzyme. MTRR A66G gene polymorphism was reported as risk factor for various diseases/disorders like—Down syndrome [10], premature coronary artery disease [11], neural tube defects [9, 12, 13], ventricular septal defect [14], Alzheimer disease [15] and schizophrenia [16], metabolic syndrome [17], non-syndromic cleft lip and palate [18] etc.

Despite the importance of this gene polymorphism in different diseases/disorders very limited data on different population/ethnicities is available. MTRR A66G polymorphism is not well studied in India especially Eastern Uttar Pradesh. The aim of the present study is to determine the frequency of clinically important MTRR A66G gene polymorphism in Eastern Uttar Pradesh population and also, try to estimate the global prevalence of MTRR A66G polymorphism by conducting a meta-analysis of all published articles.

Materials and Methods

Samples

Total 1000 unrelated healthy individuals were selected for the present study from the different parts of Eastern Uttar Pradesh. The ethical clearance for the present study was taken from the Institutional Ethics Committee of Veer Bahadur Singh Purvanchal University, Jaunpur, India. The informed written consent along with detailed demographic data was collected from all subjects.

Genomic DNA Extraction

Three milliliters blood samples was collected in EDTA coated vials from each subject and genomic DNA was extracted by the method of Bartlett and White [19]. The extracted genomic DNA was stored at − 20 °C for further analysis.

Genotyping

MTRR A66G gene polymorphism was identified by the PCR–RFLP method as described by Wilson et al. [9]. Genomic DNA was amplified with MTRR A66G region specific primers and amplicon was digested with 10U of NdeI for 12 h at 37 °C and separated on 4% agarose gel. For quality control, 10% of samples (randomly selected) were re-genotyped and no discrepancy in genotypes were found.

Allele frequencies were calculated by gene count method and χ² test was performed to test Hardy–Weinberg Equilibrium with respect to each population. All statistical analysis was done by statistical software WinPepi (version 9.9) [20].

Meta-analysis

Searched Strategy and Identification of Studies

Different databases (PubMed, Science Direct and Springer link) were searched for the eligible articles using keywords ‘‘MTRR’’, ‘‘methionine synthase reductase’’, and ‘‘A66G’’. In the present meta-analysis, we included only those articles where MTRRA66G gene polymorphism were analyzed in healthy subjects. Back references of the included articles were also scrutinized for additional studies which might be escaped from searched databases.

Inclusion and Exclusion Criteria

All selected studies for present meta-analysis should fulfill the following inclusion criteria: (1) the study should be original; and (2) MTRR AA66G genotypes or allele numbers should be reported in the study. At the same time a study was excluded if—(1) case–control; (2) case reports, reviews or letter to editor etc.

Data Extraction

First author’s family name, publication year, country of study, population/ethnic group, and number of alleles and/or genotypes were extracted from all the eligible studies. If a study is multicentric or included samples from different populations/countries/ethnicities then each population/country sample was treated as a separate study.

Statistical Analysis

Individual prevalence proportion (PP) (by dividing the number of alleles/genotypes from the total number of alleles/sample sizes) along with 95% confidence interval (CI) were calculated for each study. All the individual PPs were then combined for the estimation of pooled PP by using either fixed effect [21] or random effect [22] model depending upon heterogeneity. Random effect model was used when the heterogeneity was high (I² > 50%) [23], otherwise fixed effect model was adopted. We have also performed the sub-group analysis based on geographical area to check the frequency at the regional level. All p values were two tailed with a significance level at 0.05. The meta-analysis was performed by Open Meta-analyst program [24]. A global A66G frequency map was created by Stat-Planet software [25] by pooling the prevalence of MTRR A66G polymorphism in different countries.

Results

Total 1000 random samples were collected from different districts of Eastern Uttar Pradesh. The mean age was 36.68 ± 16.49 years. Out of total 1000 random samples 528 samples were male and 472 samples were female. MTRR specific primers produced 66 bp long amplicon after PCR (Fig. 1). G allele (66 bp long amplicon) remain uncut after NdeI restriction enzyme digestion and A allele produced two fragments of 44 bp, and 22 bp after NdeI digestion. After digestion, GG homozygotes produced single band (66 bp), AA genotype produced two bands (44 bp, and 22 bp). and AG heterozygote produced three bands (66 bp, 44 bp, and 22 bp) (Fig. 2). On the basis of number and size of band genotypes were identified.

Fig. 1.

MTRR A66G amplicon with 100 bp DNA ladder in lane 1 and 66 bp long PCR amplicon in lane 2-8

Fig. 2.

Gel showing NdeI digested different MTRR A66G genotypes: lane 1 contains 100 bp DNA ladder; lane 2, 4 and 8 contain GG; while lane 3, 5, 6 and 7 contains AG genotype

The number of AA, AG and GG genotype was 95 (9.5%), 503 (50.3%) and 402 (40.2%) respectively. The number of A and G alleles was 693 (34.65%) and 1307 (65.35%) respectively (Table 1). The population was not in Hardy–Weinberg equilibrium (χ² = 12.25, p = 0.0004). No difference was observed in the samples on stratification on the basis of gender. The frequency of G allele was 65.34% and 65.36% in males and females respectively.

Table 1.

MTRR A66G genotype distribution in all samples, gender wise distribution of samples, number of genotypes, number of alleles, χ² and p value

Sample	Number	Age (mean ± SD)	Genotype						Number of alleles				χ2, p value
			AA		AG		GG		A		G
			No.	Freq	No.	Freq	No.	Freq	No.	Freq	No.	Freq
Male	528	36.68 ± 16.49	48	0.09	270	0.51	210	0.40	366	0.35	690	0.65	8.78, 0.003
Female	472	36.89 ± 17.70	47	0.09	233	0.50	192	0.41	327	0.34	617	0.65	3.83, 0.05
Total	1000	36.44 ± 15.03	95	0.10	503	0.50	402	0.40	693	0.35	1307	0.65	12.25, 0.0004

No. number, SD standard deviation, Freq frequency

Meta-analysis

Characteristic of Eligible Studies

Our search criteria retrieved a total of 615 articles. We excluded case–control studies, reviews, letter to editor, animal studies and observational studies etc. After applying exclusion and inclusion criteria, only 16 articles with 20,921 samples were found suitable to include in the meta-analysis (including present study). In included 16 articles—three articles were published from North America [26–28], three articles from Europe [5, 29, 30], eight studies were investigated from Asia [31–37, present study], and two studies were published from South America [38, 39]. Rady et al. [26], investigated A66G polymorphism in four different populations, so we included four populations as separate studies. Similarly, in the study of Rai et al. [34], two different populations were genotyped, authors treated both samples as separate studies (Table 2). Finally, total 20 studies were included in the present meta-analysis.

Table 2.

Details of 16 included studies

Author	Country	Sample size	Genotype			Number of allele		Allelic frequency		Reference
			AA	AG	GG	A	G	A	G
Asia
Rai et al. [31] (South)	India	294	5	184	105	194	394	0.32	0.67	Indian J Hum Genet 17(1):S48–S53
Rai et al. [33] (North)	India	104	10	67	27	87	121	0.42	0.58	Biotechnology 10(20):220–223
Ghodke et al. [32] (West)	India	144	37	71	36	145	143	0.50	0.50	Indian J Med Res 133:274–279
Rai et al. [34] (Yadav)	India	50	6	30	14	42	58	0.42	0.58	Indian J Med Sci 66:136–140
Rai et al. [34] (SC)	India	50	6	26	18	38	62	0.38	0.62	Indian J Med Sci 66:136–140
Rai et al. [35] (Muslim)	India	56	5	23	28	33	79	0.29	0.71	Indian J Hum Genet 19(2):183–187
Yang et al. [36]	China	14,405	7945	5508	952	21,398	7412	0.74	0.25	PLoS ONE 8(3):e57917
Ni et al. [37]	China	300	8	274	18	290	310	0.48	0.52	Genet Test Mol Biomarkers 22(3):1–6
Present study	India	1000	95	503	402	693	1307	0.34	0.65	–
Europe
Gaughan et al. [29]	Ireland	601	172	321	105	665	531	0.55	0.44	Altherosclerosis 157:451–456
Zijno et al. [5]	Italy	191	40	101	33	181	167	0.52	0.47	Carcinogenesis 24(6):1097–1103
Gra et al. [30]	Russia	352	66	155	131	287	417	0.40	0.59	Genet Test Mol Biomarkers 14(3):329–342
North America
Rady et al. [26] (Ashkenazi-Jewish)	USA	123	41	58	24	140	106	0.56	0.43	Am J Med Genet 107:162–168
Rady et al. [26] (African-American)	USA	97	41	46	10	128	66	0.65	0.34	Am J Med Genet 107:162–168
Rady et al. [26] (Caucasian)	USA	159	33	79	47	145	173	0.45	0.54	Am J Med Genet 107:162–168
Rady et al. [26] (Hispanic)	USA	96	48	41	7	137	55	0.71	0.28	Am J Med Genet 107:162–168
Vaughn et al. [27]	USA	360	70	188	89	328	366	0.47	0.52	J Nutr 134: 2985–2990
Tsai et al. [28]	USA	1689	332	784	573	1448	1930	0.42	0.57	Mol Genet Metabol 98:181–186
South America
Barbosa et al. [38]	Brazil	100	31	46	23	54	46	0.54	0.46	Clinica Chimica Acta 388:139–147
Steluti et al. [39]	Brazil	750	267	336	147	870	630	0.58	0.42	Nutrients 9:539

Meta-analysis

The result of the meta-analysis showed that the world-wide frequency of G allele was 49.4% (95% CI 40.6–58.1, p ≤ 0.001; I² = 99.48%) and 33.1% (95% CI 32.7–33.5, p ≤ 0.001) by adopting random effect and fixed effect model respectively. The frequency of GG genotype was 24.3% (95% CI 17.8–30.9, p ≤ 0.001; I² = 98.74%) by random effect model and 9.10% (95% CI 8.70–9.40, p ≤ 0.001) by fixed effect model (Table 3, Fig. 3). Heterogeneity was high, so random effect model was adopted.

Table 3.

Summary estimates for the prevalence proportion (PP) of MTRR A66G in alleles and genotypes, the significance level (p value) of heterogeneity test (Q test), and the I² value

Population	FE Estimate (95% CI)	RE Estimate (95% CI)	I2	p (Q)
All
G	33.1 (32.7–33.5), < 0.001	49.4 (40.6–58.1), < 0.001	99.48	< 0.001
A	66.5 (66.1–67.0), < 0.001	47.5 (38.5–56.5), < 0.001	99.51	< 0.001
GG	9.10 (8.70–9.40), < 0.001	24.3 (17.8–30.9), < 0.001	98.74	< 0.001
AG	43.6 (42.9–44.2), < 0.001	51.9 (44.8–58.9), < 0.001	98.39	< 0.001
AA	31.6 (31.0–32.1), < 0.001	22.8 (11.1–34.5), < 0.001	99.72	< 0.001
American (North)
G	39.1 (36.8–41.4), < 0.001	45.0 (36.5–53.5), < 0.001	95.9	< 0.001
A	46.3 (45.0–47.7), < 0.001	54.4 (45.9–62.8), < 0.001	95.84	< 0.001
GG	26.9 (25.2–28.6), < 0.001	21.0 (11.2–30.7), < 0.001	96.04	< 0.001
AG	47.4 (45.4–49.3), < 0.001	47.5 (45.4–49.6), < 0.001	4	0.391
AA	21.5 (20.0–23.1), < 0.001	29.7 (22.2–37.2), < 0.001	91.77	< 0.001
American (South)
G	53.2 (51.8–54.5), < 0.001	32.7 (14.1–51.3), < 0.001	97.1	< 0.001
A	53.6 (51.3–55.9), < 0.001	42.6 (12.3–73.0), 0.006	98.81	< 0.001
GG	2.00 (1.73–2.26), < 0.001	20.0 (17.3–22.6), < 0.001	0	0.445
AG	44.9 (41.6–48.3), < 0.001	44.9 (41.6–48.3), < 0.001	0	0.821
AA	35.0 (31.8–38.2), < 0.001	35.0 (31.8–38.2), < 0.001	0	0.352
Asian
G	29.5 (29.0–30.0), < 0.001	56.4 (39.5–73.3), < 0.001	99.62	< 0.001
A	70.5 (70.0–71.0), < 0.001	43.6 (26.7–60.5), < 0.001	99.62	< 0.001
GG	7.50 (7.10–7.90), < 0.001	27.7 (1.66–38.8), < 0.001	98.82	< 0.001
AG	42.5 (41.8–43.2), < 0.001	56.7 (40.7–72.6), < 0.001	99.29	< 0.001
AA	33.4 (32.8–34.1), < 0.001	15.3 (− 5.50 to 36.1), 0.151	99.88	< 0.001
European
G	48.8 (46.8–50.8), < 0.001	49.1 (38.8–59.3), < 0.001	95.67	< 0.001
A	49.5 (47.4–51.5), < 0.001	47.9 (38.4–57.4), < 0.001	94.93	< 0.001
GG	21.7 (19.3–24.0), < 0.001	23.9 (11.7–36.2), < 0.001	95.68	< 0.001
AG	50.4 (47.5–53.3), < 0.001	50.1 (43.8–56.4), < 0.001	76.33	0.015
AA	23.7 (21.2–26.1), < 0.001	22.9 (16.3–29.5), < 0.001	85.36	0.001

FE fixed effect, RE random effect, CI confidence intervals, I² inconsistency between studies, Q Cochran’s test

Fig. 3.

Random effect forest plot of G allele in European, North American, South American and Asian, population

Sub-group Analysis

The sub-group meta-analyses were performed on the basis of the geographical regions. In Asia the frequency of the G allele was 56.4% (95% CI 39.5–73.3, p ≤ 0.001; I² = 99.62%) and the frequency of GG genotype was 27.7% (95% CI 1.66–38.8, p ≤ 0.001; I² = 98.82%) (Table 3; Fig. 4), in Europe the frequency of G allele was 49.1% (95% CI 38.8–59.3, p ≤ 0.001; I² = 95.67%) and frequency of GG genotype was 23.9% (95% CI 11.7–36.2, p ≤ 0.001; I² = 95.68%), (Table 3; Fig. 4), in North America the frequency of G allele was 45.0% (95% CI 36.5–53.5, p ≤ 0.001; I² = 95.9%) and frequency of GG genotype was 21.0% (95% CI 11.2–30.7, p ≤ 0.001; I² = 96.04%) (Table 3; Fig. 4), in South America the frequency of G allele was 32.7% (95% CI 14.1–51.3, p ≤ 0.001; I² = 97.1%) and frequency of GG genotype was 2.0% (95% CI 1.73–2.26, p ≤ 0.001; I² = 0%) (Table 3; Fig. 4).

Fig. 4.

Random effect forest plot of GG genotype in European, North American, South American and Asian population

Discussion

The frequency of G allele in the Eastern Uttar Pradesh population was observed as 0.65 by PCR–RFLP analysis of 1000 blood samples and the global frequency of G allele was calculated 46.3% by meta-analysis. Although MTRR A66G gene polymorphism is reported to be associated with a number of diseases/disorders (Down syndrome, psychiatric disorders, metabolic disorders and different types of cancers) but this polymorphism is not much explored and only limited data are available worldwide like—46% in Brazil [38], 25% in China [36], 44% in Ireland [29], 47% in Italy [5], 59% in Russia [30] and 42–57% in USA [26–28]. The pooled meta-analysis results showed that the frequency of G allele varies in different continents—49.1% in Europe, 45% in North America, 32.7% in South America and 56.4% in Asia. All the studies reporting this polymorphism from different countries revealed that the frequency of the two alleles i.e. A and G were found nearly similar in all the populations except a study from China [36] and in Hispanic population of USA [26] (Figs. 5, 6).

Fig. 5.

Map showing global distribution of G allele. The dark colour represents the higher frequency of the G allele in comparison to the light colour and gray colour shows that the data for those countries are not available

Fig. 6.

Map showing global distribution of GG genotype. The dark colour represents the higher frequency of the GG genotype in comparison to the light colour and gray colour shows that the data for those countries are not available

Pooled Indian studies analysis revels that the frequency of G allele and GG genotype in India is 61.7% (95% CI 56.8–66.6, p ≤ 0.001; I² = 82.64%) and 34.1% (95% CI 28.1–40.1, p ≤ 0.001; I² = 78.42%) respectively. India is divided in sub-regions as per the details of the studied population viz. North, South, and West and the frequency of G allele is 63.3%, 67.0% and 49.7% respectively. The frequency of G allele in Eastern Uttar Pradesh population is nearly similar to the frequency reported from South India [31] and higher then West India [32].

Meta-analysis is a well-established statistical tool used for combining the data of small sample sized individual studies. Meta-analysis increases the power of study and decreases type I and II errors. During past 2 decades, a number of meta-analyses were published, which assessed the polymorphism of small effect genes as risk factor for different diseases and disorder e.g. Down syndrome [40, 41], neural tube defects [42], Glucose 6-phosphate dehydrogenase deficiency [43], depression [44], cleft lip and palate [45], Alzheimer’s disease [46], male infertility [47], breast cancer [48, 49], colorectal cancer [50], esophageal cancer [51], prostate cancer [52] and digestive tract cancer [53] etc.

The present meta-analysis has a number of merits—(1) meta-analysis combined the data of the healthy individuals for the prevalence of MTRR A66G gene polymorphism; (2) no publication bias was found. At the same time there are some limitation of the meta-analysis like–(1) we searched only few databases; (2) only those studies were included which contains random samples, (3) presence of higher heterogeneity.

Conclusions

Results of present meta-analysis showed that the global frequency of MTRR A66G polymorphism was 49.4% and in Asian population the frequency of G allele was calculated as 56.4%. The results of 1000 samples analyzed in current study showed A and G allele frequency as 35% and 65% respectively, which is higher than the overall Indian G allele frequency (61.7%) calculated by meta-analysis. The result of this study will enrich the existing data of MTRR A66G gene polymorphism and can serve as a basis for further associative investigations on the role of MTRR A66G gene polymorphism in susceptibility to different diseases/disorders in different ethnic populations.

Abbreviations

MTRR

Methionine synthase reductase

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.