Literature DB >> 27089387

Geographical and Ethnic Distributions of the MTHFR C677T, A1298C and MTRR A66G Gene Polymorphisms in Chinese Populations: A Meta-Analysis.

Xingmin Wang1, Jinjian Fu1, Qianxi Li1, Dingyuan Zeng1.   

Abstract

BACKGROUND: The geographical and ethnic distributions of the polymorphic methylenetetrahydrofolate reductase (MTHFR) mutations (C677T and A1298C) and methionine synthase reductase (MTRR) mutation (A66G) remain heterogeneous in China. The goal of this study was to estimate the pooled frequencies of the alleles and associated genotypes of these gene polymorphisms among healthy populations in Mainland China. OBJECTIVE AND METHODS: We systematically reviewed published epidemiological studies on the distributions of 3 genetic variants in Chinese healthy populations living in Mainland China through a meta-analysis. The relevant electronic databases were searched. All of the raw data of the eligible citations were extracted. The frequency estimates were stratified by geography, ethnicity and sex.
RESULTS: Sixty-six studies were identified with a total of 92277 study participants. The meta-analysis revealed that the frequencies of the MTHFR C677T, A1298C, and MTRR A66G gene polymorphisms varied significantly between different ethnic groups and along geographical gradients. The frequencies of the 677T allele and 677TT genotype increased along the southern-central-northern direction across Mainland China (all Pvalues≤0.001). The frequencies of the 1298C, 1298CC, 66G and 66GG genotypes decreased along the south-central-north direction across the country (all Pvalues≤0.001).
CONCLUSIONS: Our meta-analysis strongly indicates significant geographical and ethnic variations in the frequencies of the C677T, A1298C, and A66G gene polymorphisms in the folate metabolism pathway among Chinese populations.

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Year:  2016        PMID： 27089387      PMCID： PMC4835080          DOI： 10.1371/journal.pone.0152414

Source DB:  PubMed          Journal:  PLoS One        ISSN： 1932-6203            Impact factor:   3.240


Introduction

Multiple epidemiological studies have demonstrated that homocysteine is an important biomarker with biological functions in the folate metabolism pathway. Hyperhomocysteinemia (HHCY) is a medical health problem characterized by elevated homocysteine concentrations in the plasma that has been identified as a key pathophysiological risk factor for a series of adverse events, including neural-tube defects, vascular dementia, pregnancy complications, cancers and psychiatric disorders [1-4]. Previous studies have revealed that the regulation of the plasma levels of homocysteine are quite complex and involve both environmental factors (such as folate acid and vitamin B12 intake) and hereditary components [5]. However, how a number of genes and hereditary determinants might contribute to HHCY remains unclear. Mutations in some key genes encoding homocysteine-metabolizing enzymes, such as methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C and methionine synthase reductase (MTRR) A66G, may contribute to the risk of the development of hyperhomocysteinemia and thus leas to clinical disorders [6]. The enzyme MTHFR catalyzes the conversion of 5,10-methylenetetrahydrofolate to 5-methyletetrahydrofolate, which is the carbon donor for the methylation of homocysteine to methionine [7]. The C677T polymorphism is a point mutation at position 677 of the MTHFR gene that causes the substitution of alanine with valine, which leads to a reduction in enzyme activity and causes mild to moderate hyperhomocysteinemia and reduces plasma folate levels. Genome-wide association studies (GWASs) have confirmed the association between the MTHFR C677T genotype and homocysteine levels in healthy populations [8]. Along with those investigations, several studies have proposed that double 677CT/1298AC heterozygosity can result in a reduction in enzymatic activity that represents an important risk factor for congenital anomalies, particularly in patients with low blood folate and vitamin B12 concentrations [9]. The frequency distributions of MTHFR and MTRR polymorphisms, especially C677T, vary substantially between different regional and ethnic groups. For example, the frequency of the 677T allele has been found to be highest in north India (16.7%) and lowest was in east India (1.1%). Moreover, the highest frequency of the 677TT genotype has been found in the Rajput population (7.8%), and this genotype is absent in the Kom, Meitei, Paite, Thadou, Kabui, Munda, Oraon and Naikda population groups in India [10]. A number of studies have investigated the C677T and A1298C in MTHFR and A66G in MTRR polymorphisms in different ethnic and geographical regions in Chinese general populations, however, the results have been irreproducible and inconclusive [11]. Accurate information about the geographical and ethnic distributions of the alleles and associated genotypes of MTHFR and MTRR in Mainland China will enable the design of proper interventions (e.g., folic acid supplementation) in the general population to reduce the rates of some medical diseases [12]. We conducted this comprehensive meta-analysis that integrated multiple studies to provide an overall assessment of the key polymorphisms in the major folate pathway genes among general Chinese populations. Sex-stratified and northern-central-southern gradients in the heterozygosities and allele frequencies were also assessed.

Materials and Methods

Literature database

The following major electronic literature databases were searched in September 2015 without language restrictions: PubMed, the Chinese National Knowledge Infrastructure (CNKI), the Chinese Wanfang Database, the Chinese VIP Database, and Google Scholar. The keywords and medical subject headings “MTHFR”, “MTRR”, “methylenetetrahydrofolate reductase”, “methionine synthase reductase”, “folate pathway’, “polymorphisms” or “SNP”, and “Chinese” or “China” were used to scan for potentially relevant studies.

Inclusion/exclusion criteria

The identified studies were eligible for inclusion if they met the following criteria: (1) published in Chinese or English, (2) the study participants were general Chinese populations who lived in Mainland China, (3) the evaluation of data related to any or all of the polymorphisms in MTHFR or MTRR in general Chinese populations, and (4) included data regarding genotype/allele counts of the C677T, A1298C and A66G polymorphisms among the population for the estimation of the frequencies and 95% confidence intervals (95% CIs). Studies were excluded if they met the following criteria: (1) reviews, lectures, editorials or correspondence letters, (2) the study participants were evaluated in terms of folate pathway gene polymorphisms associated with relevant diseases, (3) duplicated studies were eliminated, and only recently published studies were ultimately selected, and (4) if the same data were published in English and Chinese, only the English-language articles were included.

Data extraction

Two authors (XM Wang and JJ Fu) independently extracted the following information: the first author’s name, publication year, investigated location, ethnic groups, age, sample source, sample size, genotyping method, genotype distribution, frequency, and 95% CI.

Statistical analysis

The Hardy-Weinberg equilibrist (HWEs) were evaluated to determine whether the MTHFR C677T and A1298C and MTRR A66G genotype distributions were in genetic equilibrium (threshold set to 0.05) [13]. Meta-analyses of the prevalences of the allele frequencies (e.g., C677T: TT vs. total genotypes) and allele contrasts (e.g., C677T: T vs. total C+T) were performed using Stata statistical software version 13.0 (Stata corporation LP, College Station, Texas, USA). A random-effects model was used to account for the pooled relevant genotype frequencies and their corresponding 95% CIs. Stratified analyses were performed according to the northern-central-southern gradient, ethnicity, and sex. The heterogeneity among the studies was evaluated with the Cochrane chi-square (x) and quantified with the I statistic [14-15]. Publication bias was evaluated using Begg’s funnel plots and Egger’s test (significant at P≤0.1) [16-17].

Results

Characteristics of the studies

In total, 495 articles were identified, of which 471 potentially relevant citations were included for further evaluation. Eventually, 68 articles (66 on the C677T, 51 on the A1298C, and 43 on the A66G polymorphisms) with a total of 92277 participants met the inclusion criteria [18-85] (Fig 1). The main characteristics of the studies on the MTHFR C677T and A1298C and MTRR A66G polymorphisms are listed in Tables 1–3, respectively. In the majority of the studies, buccal cells were obtained and tested with real-time polymerase chain reaction (RT-PCR); otherwise, blood samples were tested with restriction fragment length polymorphism (RFLP) analysis. The genotype frequencies indicated that all of the polymorphisms were in HWE in all of the samples.
Fig 1

Flow chart of the study selection process.

Table 1

Distribution of the MTHFR C677T polymorphism among populations in China.

AuthorPublicationyearLocationEthnicgroupAgeSampleSample collectionSample size(male/female)MethodGenotypeTallelic
CCCTTT
Yu JM2000mixedmixednot givenbloodconvenient200RFLP8410016132
Pei LJ2000mixedmixednot givenbloodpopulational-based277RFLP9712654234
Zhu HP1998mixedmixednot givenbloodconvenient117RFLP50501784
Yang BH2001AnhuiHan20–55bloodconvenient55(30/25)RFLP19211551
Chen SQ2002GuangdongHanaverage 40bloodconvenient143(68/75)RFLP9050356
Sun WP2003ShannxiHan37–78bloodpopulational-based96(58/38)RFLP26531787
Shen LP2005Guangxinot given23–34bloodconvenient200(female)RFLP119681394
Xiao Y2005Guizhoumixednot givenbloodpopulational-based317(138/179)RFLP221906102
Zhang CS2005ShandongHan44.7±7.5bloodconvenient86(42/44)RFLP114233108
Li AF2007HenanHan56±9.8bloodpopulational-based500(274/226)RFLP163173164501
Dai XJ2008Ningxiamixed18–22bloodconvenient315(124/191)RFLP4722147315
Mao FR2008mixedmixednot givenbloodpopulational-based1015RFLP43050580665
Chen F2009HenanHan35–76bloodconvenient495(320/175)RFLP181182132446
Shan KR2009GuizhouMiaonot givenbloodpopulational-based108RFLP8817323
Chen YX2010ShanxiHan25–35bloodconvenient50(female)RFLP6242064
He XM2010mixedHannot givenbloodpopulational-based1017(female)RFLP355422220882
Jiang HO2010HunanHan20–70bloodpopulational-based120RFLP64411571
Zhang QF2010Hainanmixed19–46buccal cellsconvenient1008(female)RT-PCR559310139588
Zhang L2010Guangximixednot givenbloodpopulational-based1466(723/743)RFLP682678106890
Lao HH2011Hainanmixednot givenbuccal cellspopulational-based11437(female)RT-PCR6678374110185777
Zhang Y2012SichuanHannot givenbuccal cellspopulational-based2573(female)RT-PCR104711713551881
Wu HZ2011AnhuiHan20–35bloodpopulational-based78(39/39)RFLP3831949
He YX2012HenanHan19–44buccal cellsconvenient1093(female)RT-PCR1984934021297
Yang Y2012JiangsuHan27.0±4.4buccal cellsconvenient2885(female)RT-PCR87713786302638
Cong YY2012ShandongHan29.4±7.7buccal cellsconvenient1041(female)RT-PCR1304574541365
Zhang YL2012ShandongHan28.7±5.8buccal cellsconvenient825(female)RT-PCR138398289976
Chen HB2012ShanxiHannot givenbloodconvenient63(31/32)RFLP10312275
Gao LJ2012GuangdongHan27.6±4.0buccal cellsconvenient359(female)RT-PCR18613439212
Du LL2013GuangxiZhuang70–104bloodpopulational-based973(339/634)RFLP67725244340
Yang BY2013mixedHan18–47buccal cellspopulational-based15357(952/14405)RT-PCR49396791362714045
Wang LN2012Xinjiangmixed19–65bloodconvenient300(144/156)RFLP5819646288
Xiu X2013ShandongHan19–40buccal cellsconvenient2934(female)RT-PCR442135411383630
Chen YX2013ShanxiHan22–73bloodconvenient192(94/98)RFLP329763223
Wang WP2013HubeiHan28.2±3.3buccal cellsconvenient2899(female)RT-PCR106913674632293
Gao H2013Hubeimixed18–53buccal cellsconvenient1902(female)RT-PCR6969023041510
Wan LJ2013YunnanHan27.5±4.0buccal cellsconvenient297(female)RT-PCR11613942223
Yan ZM2013HainanHan27.2±5.3buccal cellsconvenient1221(female)RT-PCR75639075540
Zhang T2013Guizhouminoritymixedbloodpopulational-based597(318/279)RT-PCR39818019218
Huang GX2013Hainanmixedmixedbuccal cellsconvenient1841(female)RT-PCR121954874696
Luo XL2014HubeiHan27.3±5.2buccal cellsconvenient1077(female)RT-PCR429482166814
Wang FX2014ShannxiHan22–35buccal cellsconvenient1508(female)RT-PCR918249341931
Hao YY2014Xinjiangmixedmixedbuccal cellsconvenient210(female)RT-PCR838641168
Yan Q2014ShandongHan28.8±3.4buccal cellsconvenient2670(female)RT-PCR49713138603033
Xing JF2014HenanHan28.2±4.2buccal cellsconvenient425(female)RT-PCR57207158523
Hu XW2015HubeiHan28.2±4.2buccal cellsconvenient3963(female)RT-PCR144318456753195
Jia XP2015SichuanHan25.4±4.3buccal cellsconvenient4865(female)RT-PCR188722437353713
Huang QH2015JiangsuHan26.5±4.3buccal cellsconvenient348(female)RT-PCR9919258308
Li JH2015HebeiHan27.3±4.9buccal cellsconvenient1267(female)RT-PCR2206174301477
Xiang CG2015SichuanHan26.0±4.8buccal cellsconvenient656(female)RT-PCR238302116534
Jiang W2014Guangximixed28.0±4.5buccal cellsconvenient948(female)RT-PCR57231561437
Ouyang QQ2014ShandongHan22–39bloodconvenient98(female)RFLP24522296
Chen XL2014GuangxiHan27.7±4.4buccal cellsconvenient564(female)RT-PCR82271211693
Ma LM2015HeilongjiangHan28.1±5.5buccal cellsconvenient455(female)RT-PCR78240137514
Tang HY2014ShandongHan27.7±3.8buccal cellsconvenient787(female)RT-PCR107373307987
Tian Y2014JiangsuHan27.0±4.8buccal cellsconvenient524(female)RT-PCR18524099438
Lu GR2014ShandongHan28.5±5.0buccal cellsconvenient1352(female)RT-PCR2016255261677
Jiao FY2014ShandongHan28.2±4.2buccal cellsconvenient529(female)RT-PCR93261175611
Gao X2014HebeiHan28.3±4.3buccal cellsconvenient860(female)RT-PCR158429273829
Luo SQ2015GuangxiMiaonot givenbuccal cellsconvenient818(female)RT-PCR59320812242
Yu YH2015JilinHan28.5±4.3buccal cellsconvenient2620(female)RT-PCR55112538162885
Li XX2015JiangsuHan26.7±3.6buccal cellsconvenient4008(female)RT-PCR129019847341431
Wang SY2015HunanHan26.7±4.6buccal cellsconvenient1701(female)RT-PCR7257622141190
Wu WQ2015JiangsuHan26.4±4.5buccal cellsconvenient644(female)RT-PCR189308147602
Mao WC2015Guizhoumixednot givenbuccal cellsconvenient1232(female)RT-PCR468416158832
Cui HL2015HenanHan28.9±4.7buccal cellsconvenient1253(female)RT-PCR2015425101562
Liu XL2014NingxiaHan29.4±5.3buccal cellsconvenient443(female)RT-PCR113228102432
Table 3

Distribution of the MTRR A66G polymorphism among populations in China.

AuthorPublicationyearLocationEthnicgroupAgeSampleSample collectionSample size (male/female)MethodGenotypeG allelic
AAAGGG
He XM2010mixedHannot givenbloodpopulational-based1017(female)RFLP56738763513
Zhang QF2010Hainanmixed19–46buccal cellsconvenient1008(female)RT-PCR51641082574
Lao HH2011Hainanmixednot givenbuccal cellspopulational-based11437(female)RT-PCR5616476310586879
Zhang Y2012SichuanHannot givenbuccal cellspopulational-based2573(female)RT-PCR13859772111399
He YX2012HenanHan19–44buccal cellsconvenient1093(female)RT-PCR62440069538
Yang Y2012JiangsuHan27.0±4.4buccal cellsconvenient2885(female)RT-PCR164210711721415
Cong YY2012ShandongHan29.4±7.7buccal cellsconvenient1041(female)RT-PCR61038150481
Zhang YL2012ShandongHan28.7±5.8buccal cellsconvenient825(female)RT-PCR45132549423
Gao LJ2012GuangdongHan27.6±4.0buccal cellsconvenient359(female)RT-PCR19614320183
Yang BY2013mixedHan18–47buccal cellspopulational-based15357(952/14405)RT-PCR8514583410097852
Xiu X2013ShandongHan19–40buccal cellsconvenient2934(female)RT-PCR170610601681396
Wang WP2013HubeiHan28.2±3.3buccal cellsconvenient2899(female)RT-PCR165010711781427
Gao H2013Hubeimixed18–53buccal cellsconvenient1902(female)RT-PCR1082697123943
Wan LJ2013YunnanHan27.5±4.0buccal cellsconvenient297(female)RT-PCR17210619144
Yan ZM2013HainanHan27.2±5.3buccal cellsconvenient1221(female)RT-PCR580528113754
Lu XC2013GuangxiZhuangmixedbuccal cellsconvenient300(female)RT-PCR8311720157
Huang GX2013Hainanmixedmixedbuccal cellsconvenient1841(female)RT-PCR8428091901189
Luo XL2014HubeiHan27.3±5.2buccal cellsconvenient1077(female)RT-PCR57942969563
Wang FX2014ShannxiHan22–35buccal cellsconvenient1508(female)RT-PCR82059592780
Hao YY2014Xinjiangmixedmixedbuccal cellsconvenient210(female)RT-PCR969123137
Yan Q2014ShandongHan28.8±3.4buccal cellsconvenient2670(female)RT-PCR145910181931404
Xing JF2014HenanHan28.2±4.2buccal cellsconvenient425(female)RT-PCR24116219200
Jia XP2015SichuanHan25.4±4.3buccal cellsconvenient4865(female)RT-PCR274817953222439
Huang QH2015JiangsuHan26.5±4.3buccal cellsconvenient348(female)RT-PCR21711812142
Li JH2015HebeiHan27.3±4.9buccal cellsconvenient1267(female)RT-PCR70549666628
Xiang CG2015SichuanHan26.0±4.8buccal cellsconvenient656(female)RT-PCR37123946331
Jiang W2014Guangximixed28.0±4.5buccal cellsconvenient948(female)RT-PCR50137671518
Chen XL2014GuangxiHan27.7±4.4buccal cellsconvenient564(female)RT-PCR32420931271
Ma LM2015HeilongjiangHan28.1±5.5buccal cellsconvenient455(female)RT-PCR24518426236
Tang HY2014ShandongHan27.7±3.8buccal cellsconvenient787(female)RT-PCR44428855398
Tian Y2014JiangsuHan27.0±4.8buccal cellsconvenient524(female)RT-PCR29819135261
Lu GR2014ShandongHan28.5±5.0buccal cellsconvenient1352(female)RT-PCR77949875648
Jiao FY2014ShandongHan28.2±4.2buccal cellsconvenient529(female)RT-PCR28520044288
Gao X2014HebeiHan28.3±4.3buccal cellsconvenient860(female)RT-PCR46033466530
Luo SQ2015GuangxiMiaonot givenbuccal cellsconvenient818(female)RT-PCR41034365473
Yu YH2015JilinHan28.5±4.3buccal cellsconvenient2620(female)RT-PCR14799771641305
Li XX2015JiangsuHan26.7±3.6buccal cellsconvenient4008(female)RT-PCR217915432861057
Wang SY2015HunanHan26.7±4.6buccal cellsconvenient1701(female)RT-PCR918668115898
Wu WQ2015JiangsuHan26.4±4.5buccal cellsconvenient644(female)RT-PCR34326041342
Mao WC2015Guizhoumixednot givenbuccal cellsconvenient1232(female)RT-PCR71843776590
Cui HL2015HenanHan28.9±4.7buccal cellsconvenient1253(female)RT-PCR70448168617
Liu XL2014NingxiaHan29.4±5.3buccal cellsconvenient443(female)RT-PCR24716927223
Hu XW2015HubeiNA28.2±4.2buccal cellsconvenient3963(female)RT-PCR224714702462962

Pooled frequencies of the allele genotypes of the three gene polymorphisms in the Chinese general population

Table 4 illustrates the summarized national estimates of the 677TT and 677T frequencies among healthy populations from 1998 to 2015. Taking all populations together, the frequencies of the 677TT genotype and the 677T allele in the healthy Chinese population were 20% (18%-23%) and 42% (38%-45%), respectively (S1 and S2 Files). Overall, the combined estimated frequencies of the 1298CC genotype and the 1298C allele in the healthy Chinese population were 5% (4%-5%) and 20% (18%-22%), respectively(S3 and S4 Files). The average frequencies of the 66GG genotype and the 66G allele in the healthy Chinese population were 7% (6%-7%) and 26% (25%-28%), respectively(S5 and S6 Files).
Table 4

Summarized prevalence with 95% confidence intervals of genetic polymorphisms in the folate pathway among Chinese populations.

PolymorphismsGenetic modelNo. of studiesNo. of provincesNo. of frequenciesInvestigated numberPrevalence(95%CI)Heterogeneity
I2(%)P
MTHFR C677TTT vs. total genotypes662318302922770.20(0.18–0.23)100.00.000
Allele contrast6623738231845540.42(0.38–0.45)100.00.000
MTHFR A1298CCC vs. total genotypes51184051856160.05(0.04–0.05)100.00.000
Allele contrast5118336491712320.20(0.18–0.22)100.00.000
MTRR A66GGG vs. total genotypes43165957846360.07(0.06–0.07)100.00.000
Allele contrast4316445081692720.26(0.25–0.28)100.00.000

Geographical distributions of the three polymorphisms in the folate pathway

The allele and genotype frequencies of the three polymorphisms according to geographical region are given in Table 5. The genotype frequencies of the MTHFR C677T and 677T alleles and the 677TT genotype frequency exhibited increases in the southern-central-northern direction in Mainland China. The frequencies of the 677T allele and the 677TT genotype increased from lower values (5% and 17%, respectively) in Guangxi, to intermediate values (12% and 32%, respectively) in Anhui, to higher values (39% and 62%, respectively) in Shandong. Taken together, the frequencies of the 677TT genotype and the 677T allele along the geographical gradient were 7% (5%-8%) and 25% (23%-27%) in southern, 19% (16%-21%) and 41% (36%-45%) in central, and 28% (25%-31%) and 53% (51%-55%) in northern China, respectively. There were significant geographical gradients in the variations in the frequencies of the 677T allele and 677TT genotype (both P values≤0.001).
Table 5

Summarized prevalence with 95% confidence intervals of genetic polymorphisms in the folate pathway with geographical distribution among Chinese populations.

PolymorphismsLatitudeGenetic modelNo. of studiesNo. of provincesNo. of frequenciesInvestigated numberPrevalence(95%CI)Heterogeneity
I2(%)P
MTHFR C677Tsouthern ChinaTT vs. total genotypes2072131273320.07(0.05–0.08)100.00.000
Allele contrast20713525546640.25(0.23–0.27)100.00.000
central ChinaTT vs. total genotypes1967588392050.19(0.16–0.21)100.00.000
Allele contrast19631075784100.41(0.36–0.45)100.00.000
northern ChinaTT vs. total genotypes27108557255690.28(0.25–0.31)100.00.000
Allele contrast271029134511380.53(0.51–0.55)100.00.000
MTHFR A1298Csouthern ChinaCC vs. total genotypes1341705266530.07(0.05–0.09)100.00.000
Allele contrast13412762533060.28(0.24–0.31)100.00.000
central ChinaCC vs. total genotypes1971432389360.04(0.03–0.04)100.00.000
Allele contrast19714182778720.18(0.17–0.19)100.00.000
northern ChinaCC vs. total genotypes197692190290.03(0.02–0.03)100.00.000
Allele contrast1975876380540.17(0.16–0.19)100.00.000
MTRR A66Gsouthern ChinaGG vs. total genotypes4340248390.08(0.06–0.10)100.00.000
Allele contrast43277096780.29(0.28–0.30)100.00.000
central ChinaGG vs. total genotypes1962710417280.06(0.06–0.07)100.00.000
Allele contrast19621068834560.25(0.23–0.27)100.00.000
northern ChinaGG vs. total genotypes2071192197590.06(0.05–0.06)100.00.000
Allele contrast2079810395180.24(0.23–0.25)100.00.000
The frequency of the MTHFR A1298C polymorphism exhibited the reverse trend; i.e., this frequency decreasing from southern to central to northern China. The pooled geographical gradient frequencies of the 1298C allele and 1298CC genotype were found to be 28% (24%-31%) and 7% (5%-9%) in southern, 18% (17%-19%) and 4% (3%-4%) in central, and 17% (16%-19%) and 3% (2%-3%) in northern China, respectively (Table 5). There were significant geographical gradients in the frequencies of the 1298C allele and 1298CC genotype (both P values≤0.001). The mean frequencies of the MTRR 66G allele and 66GG genotype decreased from 29% (28%-30%) and 8% (6%-10%) in southern China, to 25% (23%-27%) and 6% (6%-7%) in central China, and 24% (23%-25%) and 6% (5%-6%) in northern China (Table 5) in a pattern similar to that observed in the gradients of the MTHFR 1298C allele and 1298CC genotype frequencies (both P values≤0.001).

The frequencies of the MTHFR C677T, A1298C, and MTRR A66G polymorphisms by ethnicity

The allele and genotype distributions of MTHFR and MTRR by ethnicity are presented in Table 6. The distributions of the MTHFR 677T allele and the 677TT genotype exhibited ethnic variations (with both P values≤0.001). The 677T allele frequencies in the minority groups (e.g., Miao, Zhuang, She, Shui, etc.) and Chinese Han were 28% (25%-31%) and 45% (41%-49%), respectively. The 677TT genotype frequencies in the minority groups and Chinese Han were 5% (4%-6%) and 22% (20%-25%), respectively.
Table 6

Summarized prevalence with 95% confidence intervals of genetic polymorphisms in the folate pathway with ethnicity distribution among Chinese populations.

PolymorphismsEthnicityGenetic modelNo. of studiesNo. of ethnic groupsNo. of provincesNo. of frequenciesInvestigated numberPrevalence(95%CI)Heterogeneity
I2(%)P
MTHFR C677TMinorityTT vs. total genotypes17191138175590.05(0.04–0.06)100.00.000
Allele contrast1719113390151180.28(0.25–0.31)100.00.000
HanTT vs. total genotypes5512216973788520.22(0.20–0.25)100.00.000
Allele contrast55122660651577040.45(0.41–0.49)100.00.000
MTHFR A1298CMinorityCC vs. total genotypes108436846690.07(0.05–0.09)100.00.000
Allele contrast1084249493380.26(0.23–0.30)100.00.000
HanCC vs. total genotypes441173228744540.04(0.03–0.05)100.00.000
Allele contrast44117282051489080.19(0.17–0.20)100.00.000
MTRR A66GMinorityGG vs. total genotypes85443647920.10(0.08–0.12)100.00.000
Allele contrast854291895840.35(0.35–0.36)100.00.000
HanGG vs. total genotypes391155210753570.06(0.05–0.07)100.00.000
Allele contrast39115383671507140.25(0.24–0.26)100.00.000
In contrast to C677T, the distribution of the A1298C polymorphism by ethnicity demonstrated the reverse trend: the 1298C allele was much more common among the minority groups [26%, (23%-30%)] than the Chinese Han [19% (17%-20%); P value≤0.001]. The 1298CC genotype exhibited similar variability with frequencies of 7% (5%-9%) in the minority groups and 4% (3%-5%) in the Chinese Han (P value ≤0.001). The frequencies of the MTRR 66G allele and 66GG genotype varied by ethnic group and geographical location. The frequency of the 66G allele was slightly higher among the minority groups [35% (35%-36%)] compared with 25% (24%-26%) among the Chinese Han group (P value ≤0.001). The frequencies of the 66GG genotype were 10% (8%-12%) in the minority groups and 6% (5%-7%) in the Chinese Han group, which were similar to those of the MTHFR A1298C polymorphism (P value ≤0.001).

The frequencies of MTHFR C677T, A1298C and MTRR A66G polymorphisms by sex

Table 7 provides the pooled frequencies of the variant alleles and genotypes of MTHFR C677T and A1298C and MTRR A66G according to sex. A total of 88255 samples with reported C677T polymorphisms were obtained. Based on all these samples, we did not find any difference between the males [19% (12%-25%)] and females [21% (19%-24%)] in terms of 677TTgenotype frequency.
Table 7

Summarized prevalence with 95% confidence intervals of genetic polymorphisms in the folate pathway with sex distribution among Chinese populations.

PolymorphismsGenderGenetic modelNo. of studiesNo. of provincesNo. of frequenciesInvestigated numberPrevalence(95%CI)Heterogeneity
I2(%)P
MTHFR C677TMaleTT vs. total genotypes11646225070.19(0.12–0.25)100.00.000
Allele contrast116238050140.49(0.41–0.58)100.00.000
FemaleTT vs. total genotypes531717311857480.21(0.19–0.24)100.00.000
Allele contrast5317690981714960.44(0.40–0.47)100.00.000
MTHFR A1298CFemaleCC vs. total genotypes41173733825320.04(0.04–0.05)100.00.000
Allele contrast4117318831650640.19(0.18–0.21)100.00.000
MTRR A66GFemaleGG vs. total genotypes42155907844160.07(0.06–0.07)100.00.000
Allele contrast4215443511688320.26(0.25–0.27)100.00.000
Only 41 studies reported the frequency of the MTHFR A1298C polymorphism and included 82532 females of reproductive age. The 1298C allele and 1298CC genotype frequencies in females were 19% (18%-21%) and 4% (4%-5%), respectively. Among the 43 articles that reported on the MTRR A66G polymorphism, 42 studies included 84416 females. The 66G allele and 66GG genotype frequencies in females were 26% (25%-27%) and 7% (6%-7%), respectively.

Publication bias

Tables 4–7 presents information related to heterogeneity and publication bias. We noted significant heterogeneity within the studies and the subgroups (all P values were ≤0.001, I = 100.0).

Discussion

Methylenetetrahydrofolate reductase (MTHFR) (C677T and A1298C) and methionine synthase reductase (MTRR) mutations (A66G) cause mild hyperhomocysteinemia and low folate level and are associated with several disorders. The geographical and ethnic distributions of these alleles and the associated genotypes are important to study worldwide. The frequencies of the MTHFR C677T and A1298C and MTRR A66G polymorphism in 68 epidemiological studies covering 23 provinces in Mainland China were pooled and investigated in the present study. Currently, there is a lack of national data regarding the prevalences of gene polymorphisms in the folate metabolism pathway in healthy general populations in China. We documented distinctive geographical and ethnic variations in the frequencies of the C677T and A1298C polymorphisms of the MTHFR gene and the A66G polymorphisms of the MTRR gene among nation-wide samples in China. Worldwide data have revealed that significant heterogeneities in the frequencies of the T allele and TT homozygosity exist in every population and even with racial groups. One investigations conducted in Texas reported that the frequency of the 677T was lowest among African-Americans (11.9%), followed by in Caucasians (32.7%) and Ashkenazi Jews (47.7%), and the highest frequency exists among the Hispanic population (47.9%) [86]. In the Chinese Han, the frequencies of the 677T allele have been found to be lowest in Hainan (24.0%) followed by Hubei (40.3%) and Jiangsu (43.5%), and the highest frequency has been observed in Shandong (63.1%) [51]. Population genetic comparisons provide an appropriate method for picturing geographical and ethnic variations and can suggest that environmental factors may exert selective pressures on genetic mutations. A north-to-south increase in the frequency of the 677T allele has been observed in Europe [87]. North-to-south increases in dietary folate intake have also been encountered in European populations [88]. Thus adequate folic acid intakes have presumed enabled increase in the MTHFR 677T frequency in these populations [89]. Economic and dietary habits might have played important roles in the spread of the 677T allele worldwide. For example, the frequency of the 677T allele is high in the USA with an average frequency of 36.2% in Texas [86]. Another study conducted in India observed the highest frequency of the 677T allele among the Sindhi population (23.8%). In contrast, the 677T allele is absent in the Kom, Thadou and Munda populations, and its average frequency is 10.1% across all 23 populations in India [10]. The low frequencies of the 677T allele among the tribal groups (i.e., the Kom, Thadou and Munda populations) may have been influenced by folate deficiencies because the majority of the population in India has a vegetarian diets that is low in vitamin B12 [10]. The populations of America carried higher frequencies of the 677T allele, which may be related to abundant nutritional statuses and particularly with folic acid and vitamin B12 supplementation, which are associated with low levels of homocysteinemia. Across all 23 of the studied provinces, we observed increases in the 677T allele and 677TT genotype frequencies in the southern-central-northern direction across Mainland China. Because high 677T allele and 677TT genotype frequencies were observed in the northern populations, we assumed that the folic acid intakes are greater in the northern populations than in the southern populations; however, the opposite pattern has been observed in nutritional studies. One such nutritional investigation revealed that the geometric mean of the blood folate concentration is lower in the northern populations than the southern populations [90]. Worldwide epidemiological data have revealed that the frequency of A1298C homozygosity varies from continent to continent. The frequencies of the 1298C allele range from 18% to 70% in East Asia, 17% to 44% in Asia, 24% to 40% in Europe, 0% to 15% in South America and 14.7% in North America [91]. The present data revealed variation in the frequency of the 1298C allele within China. In contrast to the distribution of 677T, the frequency of the 1298C allele was found to be the lowest in northern China [18% (17%-19%)], intermediate in central China [18% (17%-19%)], and highest in southern China [28% (24%-31%)]. The mean frequency of the 1298C allele was 20% (18%-22%). Based on all 8 of the investigated minority ethnic populations (e.g., the She, Xibo, and Uygur), the minority ethnic populations seemed to carry greater 1298C allele frequencies than the Chinese Han population. Notably, the frequency of the 1298C allele has been reported to vary between different ethnic populations worldwide, and the lowest frequency has been found in Indians (10%) [92] followed by the Chinese (18.4%) [51] and Tamils (35%) [93], and the highest frequency has been observed in the Lebanese [94]. Although A1298C homozygotes do not exhibit elevated blood homocysteinemialevels, many investigations have revealed that compound heterozygotes for C677T/ A1298C may be at risk for hyperhomocysteinemia and low folate levels, which can contribute to many disorders, such as neutral tube defects [6] and abortions [95]. Because lifestyle and environmental factors, such as folate supplementation, vary across different ethnic populations and may influence the frequencies of the C677T and A1298C alleles, these factors cannot be ruled out when considering the influences of environmental-genetic interactions on the distributions of MTHFR gene polymorphisms. Our pooled data revealed that the frequencies of the 66G allele and 66GG genotype exhibited variations across geographical gradients and ethnic populations. Globally, the distributions of the MTRR 66G allele and 66GG genotype frequencies also exhibit geographical and ethnic variations. For example, the frequencies of the 66G allele have been reported to be 58% in the Yadav, 62% in the Scheduled Castes, and 71% in the rural Sunni Muslim population in Uttar Pradesh in India [96,97]. Our study observed a 66GG genotype frequency of 7% across Mainland China, which is much lower than those in Brazil (23%), Australia (10%), and Ireland (17.5%) [98-100]. MTRR is involved in the homocysteine and folate metabolic pathway via its activation of methionine synthase via reductive methylation and is consequently a critical determinant of homocysteinemia levels [101]. Therefore, the MTRR A66G mutation may indirectly contribute to many medical disorders, such as neural tube defects and congenital heart disease [102], due to its key role in the folate metabolism pathway. However, due to limited sample sizes and the lower frequency of studies of the A66G polymorphisms in MTRR, no solid evidence has been found to relate the MTRR A66G variant with the risks of diseases. Long-term data and larger sample sizes are necessary to determine the real connections between the distribution of the A66G variant and the risks of diseases.

Conclusions

In conclusion, our meta-analysis revealed significant geographical variations in the frequencies of the MTHFR C677T and A1298C and MTRR A66G polymorphisms in the folate metabolism pathway between different ethnic populations in China. Our findings provide an overall picture of these three genetic polymorphisms in the folate metabolism pathway among the general populations in Mainland China, and these evidence-based genomic data should be integrated into medical and public health practices.

The average frequencies of the 677TT genotype in the healthy Chinese population.

(TXT) Click here for additional data file.

The average frequencies of the 677T allele in the healthy Chinese population.

(TXT) Click here for additional data file.

The average frequencies of the 1298CC genotype in the healthy Chinese population.

(TXT) Click here for additional data file.

The average frequencies of the 1298C allele in the healthy Chinese population.

(TXT) Click here for additional data file.

The average frequencies of the 66GG genotype in the healthy Chinese population.

(TXT) Click here for additional data file.

The average frequencies of the 66G allele in the healthy Chinese population.

(TXT) Click here for additional data file.
Table 2

Distribution of the MTHFR A1298C polymorphism among populations in China.

AuthorPublicationyearLocationEthnicgroupAgeSampleSample collectionSample size (male/female)MethodGenotypeC allelic
AAACCC
Zhu HP1998mixedmixednot givenbloodconvenient117RFLP6941755
Sun WP2003ShannxiHan37–78bloodpopulational-based96(58/38)RFLP6132338
Xiao Y2005Guizhoumixednot givenbloodpopulational-based317(138/179)RFLP10018433250
Zhang CS2005ShandongHan44.7±7.5bloodconvenient86(42/44)RFLP6719019
Mao FR2008mixedmixednot givenbloodpopulational-based998RFLP391385222829
Chen F2009HenanHan35–76bloodconvenient495(320/175)RFLP3871053111
He XM2010mixedHannot givenbloodpopulational-based1017(female)RFLP64932246414
Zhang QF2010Hainanmixed19–46buccal cellsconvenient1008(female)RT-PCR58534281504
Lao HH2011Hainanmixednot givenbuccal cellspopulational-based11437(female)RT-PCR648141458115767
Zhang Y2012SichuanHannot givenbuccal cellspopulational-based2573(female)RT-PCR16128001611122
Wu HZ2011AnhuiHan20–35bloodpopulational-based78(39/39)RFLP4630234
He YX2012HenanHan19–44buccal cellsconvenient1093(female)RT-PCR79826926321
Yang Y2012JiangsuHan27.0±4.4buccal cellsconvenient2885(female)RT-PCR1993791101993
Cong YY2012ShandongHan29.4±7.7buccal cellsconvenient1041(female)RT-PCR82220415234
Zhang YL2012ShandongHan28.7±5.8buccal cellsconvenient825(female)RT-PCR62717820218
Gao LJ2012GuangdongHan27.6±4.0buccal cellsconvenient359(female)RT-PCR22111226164
Yang BY2013mixedHan18–47buccal cellspopulational-based13473RT-PCR900039445295002
Xiu X2013ShandongHan19–40buccal cellsconvenient2934(female)RT-PCR222467238744
Wang WP2013HubeiHan28.2±3.3buccal cellsconvenient2899(female)RT-PCR19018661321130
Gao H2013Hubeimixed18–53buccal cellsconvenient1902(female)RT-PCR128355861680
Wan LJ2013YunnanHan27.5±4.0buccal cellsconvenient297(female)RT-PCR194958111
Yan ZM2013HainanHan27.2±5.3buccal cellsconvenient1221(female)RT-PCR69943587609
Zhang T2013Guizhouminoritymixedbloodpopulational-based597(318/279)RT-PCR31124343329
Wang P2013XinjiangmixedNot givenbuccal cellsconvenient300(female)RT-PCR204915101
Huang GX2013Hainanmixedmixedbuccal cellsconvenient1841(female)RT-PCR999694148990
Luo XL2014HubeiHan27.3±5.2buccal cellsconvenient1077(female)RT-PCR70234728403
Wang FX2014ShannxiHan22–35buccal cellsconvenient1508(female)RT-PCR542912541020
Hao YY2014Xinjiangmixedmixedbuccal cellsconvenient210(female)RT-PCR135641186
Yan Q2014ShandongHan28.8±3.4buccal cellsconvenient2670(female)RT-PCR193668549783
Xing JF2014HenanHan28.2±4.2buccal cellsconvenient425(female)RT-PCR3161024110
Hu XW2015HubeiNA28.2±4.2buccal cellsconvenient3963(female)RT-PCR266111681341436
Jia XP2015SichuanHan25.4±4.3buccal cellsconvenient4865(female)RT-PCR309615552141983
Huang QH2015JiangsuHan26.5±4.3buccal cellsconvenient348(female)RT-PCR23110610126
Li JH2015HebeiHan27.3±4.9buccal cellsconvenient1267(female)RT-PCR94729624344
Xiang CG2015SichuanHan26.0±4.8buccal cellsconvenient656(female)RT-PCR42820523251
Jiang W2014Guangximixed28.0±4.5buccal cellsconvenient948(female)RT-PCR53534469482
Chen XL2014GuangxiHan27.7±4.4buccal cellsconvenient564(female)RT-PCR40914411166
Ma LM2015HeilongjiangHan28.1±5.5buccal cellsconvenient455(female)RT-PCR3361109128
Tang HY2014ShandongHan27.7±3.8buccal cellsconvenient787(female)RT-PCR60716812192
Tian Y2014JiangsuHan27.0±4.8buccal cellsconvenient524(female)RT-PCR36114518181
Lu GR2014ShandongHan28.5±5.0buccal cellsconvenient1352(female)RT-PCR102729728353
Jiao FY2014ShandongHan28.2±4.2buccal cellsconvenient529(female)RT-PCR40011712141
Gao X2014HebeiHan28.3±4.3buccal cellsconvenient860(female)RT-PCR62421620435
Luo SQ2015GuangxiMiaoNAbuccal cellsconvenient818(female)RT-PCR43532261444
Li XX2015JiangsuHan26.7±3.6buccal cellsconvenient4008(female)RT-PCR27551152101768
Wang SY2015HunanHan26.7±4.6buccal cellsconvenient1701(female)RT-PCR104357682740
Wu WQ2015JiangsuHan26.4±4.5buccal cellsconvenient644(female)RT-PCR45616721209
Mao WC2015Guizhoumixednot givenbuccal cellsconvenient1232(female)RT-PCR80338049478
Cui HL2015HenanHan28.9±4.7buccal cellsconvenient1253(female)RT-PCR94729016322
Liu XL2014NingxiaHan29.4±5.3buccal cellsconvenient443(female)RT-PCR30512315153
Yu YH2015JilinHan28.5±4.3buccal cellsconvenient2620(female)RT-PCR191263969777
  39 in total

1.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

2.  No association between MTHFR A1298C and MTRR A66G polymorphisms, and MS in an Australian cohort.

Authors:  A L Szvetko; J Fowdar; J Nelson; N Colson; L Tajouri; P A Csurhes; M P Pender; L R Griffiths
Journal:  J Neurol Sci       Date:  2006-11-20       Impact factor: 3.181

3.  Operating characteristics of a rank correlation test for publication bias.

Authors:  C B Begg; M Mazumdar
Journal:  Biometrics       Date:  1994-12       Impact factor: 2.571

4.  The 677 C-->T mutation in the methylenetetrahydrofolate reductase (MTHFR) gene in five Chinese ethnic groups.

Authors:  J Yu; B Chen; G Zhang; S Fu; P Li
Journal:  Hum Hered       Date:  2000 Jul-Aug       Impact factor: 0.444

5.  A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects?

Authors:  N M van der Put; F Gabreëls; E M Stevens; J A Smeitink; F J Trijbels; T K Eskes; L P van den Heuvel; H J Blom
Journal:  Am J Hum Genet       Date:  1998-05       Impact factor: 11.025

6.  Geographical, seasonal and gender differences in folate status among Chinese adults.

Authors:  Ling Hao; Jing Ma; Meir J Stampfer; Aiguo Ren; Yihua Tian; Yi Tang; Walter C Willett; Zhu Li
Journal:  J Nutr       Date:  2003-11       Impact factor: 4.798

7.  The role of hyperhomocysteinemia in neurological features associated with coeliac disease.

Authors:  Alessandro Ferretti; Pasquale Parisi; Maria Pia Villa
Journal:  Med Hypotheses       Date:  2013-07-26       Impact factor: 1.538

8.  Polymorphisms in MTHFR, MS and CBS genes and homocysteine levels in a Pakistani population.

Authors:  Mohsin Yakub; Naushad Moti; Siddiqa Parveen; Bushra Chaudhry; Iqbal Azam; Mohammad Perwaiz Iqbal
Journal:  PLoS One       Date:  2012-03-21       Impact factor: 3.240

9.  Genetic variant in MTRR, but not MTR, is associated with risk of congenital heart disease: an integrated meta-analysis.

Authors:  Bingxi Cai; Ti Zhang; Rong Zhong; Li Zou; Beibei Zhu; Wei Chen; Na Shen; Juntao Ke; Jiao Lou; Zhenling Wang; Yu Sun; Lifeng Liu; Ranran Song
Journal:  PLoS One       Date:  2014-03-04       Impact factor: 3.240

10.  MTRR A66G polymorphism among two caste groups of Uttar Pradesh (India).

Authors:  Vandana Rai; Upendra Yadav; Pradeep Kumar
Journal:  Indian J Med Sci       Date:  2012 May-Jun
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  12 in total

1.  Ethnogeographic prevalence and implications of the 677C>T and 1298A>C MTHFR polymorphisms in US primary care populations.

Authors:  James S Graydon; Karla Claudio; Seth Baker; Mohan Kocherla; Mark Ferreira; Abiel Roche-Lima; Jovaniel Rodríguez-Maldonado; Jorge Duconge; Gualberto Ruaño
Journal:  Biomark Med       Date:  2019-06-03       Impact factor: 2.851

2.  MTHFR (C677T, A1298C), FV Leiden polymorphisms, and the prothrombin G20210A mutation in arterial ischemic stroke among young tunisian adults.

Authors:  Lamia M'barek; Salma Sakka; Fatma Meghdiche; Dhaker Turki; Khadija Maalla; Mariem Dammak; Choumous Kallel; Chokri Mhiri
Journal:  Metab Brain Dis       Date:  2021-01-05       Impact factor: 3.584

3.  No evidence for association of MTHFR 677C>T and 1298A>C variants with placental DNA methylation.

Authors:  Giulia F Del Gobbo; E Magda Price; Courtney W Hanna; Wendy P Robinson
Journal:  Clin Epigenetics       Date:  2018-03-13       Impact factor: 6.551

4.  5-HTTLPR and MTHFR 677C>T polymorphisms and response to yoga-based lifestyle intervention in major depressive disorder: A randomized active-controlled trial.

Authors:  Madhuri R Tolahunase; Rajesh Sagar; Rima Dada
Journal:  Indian J Psychiatry       Date:  2018 Oct-Dec       Impact factor: 1.759

5.  Methylenetetrahydrofolate Reductase Polymorphisms and Pregnancy Outcome.

Authors:  Mert Turgal; Fatma Gumruk; Ergun Karaagaoglu; Mehmet Sinan Beksac
Journal:  Geburtshilfe Frauenheilkd       Date:  2018-09-14       Impact factor: 2.915

6.  Impact of methylenetetrahydrofolate reductase C677T polymorphism on the efficacy of photodynamic therapy in patients with neovascular age-related macular degeneration.

Authors:  Francesco Parmeggiani; Carla Enrica Gallenga; Ciro Costagliola; Francesco Semeraro; Mario R Romano; Roberto Dell'Omo; Andrea Russo; Katia De Nadai; Donato Gemmati; Sergio D'Angelo; Elena Bolletta; Francesco Saverio Sorrentino
Journal:  Sci Rep       Date:  2019-02-22       Impact factor: 4.379

7.  The association between 5, 10 - methylenetetrahydrofolate reductase and the risk of unexplained recurrent pregnancy loss in China: A Meta-analysis.

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Journal:  Medicine (Baltimore)       Date:  2021-04-30       Impact factor: 1.817

8.  Homocysteine and all-cause mortality in hypertensive adults without pre-existing cardiovascular conditions: Effect modification by MTHFR C677T polymorphism.

Authors:  Benjamin Xu; Xiangyi Kong; Richard Xu; Yun Song; Lishun Liu; Ziyi Zhou; Rui Gu; Xiuli Shi; Min Zhao; Xiao Huang; Mingli He; Jia Fu; Yefeng Cai; Ping Li; Xiaoshu Cheng; Changyan Wu; Fang Chen; Yan Zhang; Genfu Tang; Xianhui Qin; Binyan Wang; Hao Xue; Yundai Chen; Ye Tian; Ningling Sun; Yimin Cui; Fan Fan Hou; Jianping Li; Yong Huo
Journal:  Medicine (Baltimore)       Date:  2017-02       Impact factor: 1.817

9.  Type 2 diabetes mellitus: distribution of genetic markers in Kazakh population.

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10.  Methylenetetrahydrofolate Reductase (MTHFR) C677T Polymorphism and Subacute Combined Degeneration: Revealing a Genetic Predisposition.

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Journal:  Front Neurol       Date:  2019-01-09       Impact factor: 4.003
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