Abstract
Background: Recently, increasing evidence has implicated methylenetetrahydrofolate reductase (MTHFR) gene mutation as a risk factor for ischemic stroke (IS) in the general population. However, studies have been inconclusive and lack evidence on specific populations. We aim to determine whether the rs1801133 (NC_000001.11 (MTHFR):g. 677C>T (p.Ala222Val) variant, we termed as MTHFR rs1801133 (677 C>T), is linked to an increased risk of IS in different age groups and ancestry groups.
Methods: The literature relevant to our study was found by searching the PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI databases. A random effect model analysis was used to calculate the pooled odds ratio (OR) and 95% confidence interval (CI) to evaluate any possible association. We conducted a subgroup analysis based on the age and ancestry groups of the included populations.
Results: As of March 2022, 1,925 citations had been identified in electronic databases, of which 96 studies involving 34,814 subjects met our eligibility criteria. A strong link was found between IS and the MTHFR gene rs1801133 (677C>T) polymorphism in all genetic models [dominant genetic model (OR = 1.47; 95%CI = 1.33–1.61; p < 0.001), recessive genetic model (OR = 1.52; 95%CI = 1.36–1.71; p < 0.001), heterozygous model (OR = 1.36; 95%CI = 1.24–1.48; p < 0.001), homozygous model (OR = 1.82; 95%CI = 1.58–2.11; p < 0.001), and T allelic genetic model (OR = 1.37; 95%CI = 1.27–1.48; p < 0.001)]. Further subgroup analyses indicated that the MTHFR rs1801133 (677C>T) variant may increase the risk of IS in Asian, Hispanic, or Latin population, middle-aged, and elderly populations (p < 0.001).
Conclusion: Our results implied that mutation of the T allele of MTHFR rs1801133 (677C>T) could be a risk factor for IS. A significant association was found among Asian, Hispanic, or Latin population, middle-aged, and elderly people.
1 Introduction
Ischemic stroke (IS) is an acute neurological deficit caused by vascular occlusion. It is one of the leading causes of death and disability worldwide (Francis et al., 2007; Malik and Dichgans, 2018; Phipps and Cronin, 2020) and is caused by a combination of environmental and genetic factors (Black et al., 2015; Prabhakaran et al., 2015; Malik et al., 2019). Several pathophysiological mechanisms are involved in the development of this condition. Hyperhomocysteinemia is reported to be independently associated with the risk of stroke (Linnebank et al., 2012). The 5,10-methylenetetrahydrofolate reductase (MTHFR) locus is mapped to chromosome 1 (1p36.3) which encodes for the dimeric proteins of 70–77 kDa subunits (Goyette et al., 1994). Folate metabolism is largely controlled by MTHFR, which catalyzes the conversion of 5,10-methylenetetrahydrofolate to 5-methylenetetrahydrofolate. 5-Methylenetetrahydrofolate provides a methyl group in the methylation reaction that transforms homocysteine into methionine (Figure 1), as well as the DNA methylation process (Brattström et al., 1998). Thus, the MTHFR enzyme activity is important for homeostasis of the serum homocysteine level.
FIGURE 1
The previous study had demonstrated that approximately 40% of the intragenic coding CpG islands were hyper-methylated, which had a higher C>T mutation rate. Also, the amino acid sequence of a protein and individual phenotypes could be changed by C>T substitutions at the CpG contexts in the protein-coding regions (Youk et al., 2020). The rs1801133 variant (NC_000001.11 (MTHFR):g. 677C>T (p.Ala222Val), also named MTHFR rs1801133 (677C>T), is a common mutant in MTHFR. The replacement of C with T at nucleotide 677 results in converting alanine to valine amino acid residue in the enzyme (Sharp and Little, 2004). Missense mutations cause a 50%–60% decrease in enzyme activity in patients who have the homozygous variant (TT) (Rozen, 199 7), which contributes to hyperhomocysteinemia (Castro et al., 2004). In addition, reduction of the MTHFR enzymatic activity would cause deficiency of folate, which is also an independent risk factor of IS (Qin et al., 2020). Moreover, when folic acid o is inadequate, the removal of homocysteine would be affected, leading to hyperhomocysteinemia and forming a vicious cycle (Liew and Gupta, 2015). Thus, it is important to determine the association between MTHFR rs1801133 (677C>T) polymorphism and the risk of IS for primary and secondary prevention of IS.
Many researchers have examined the relationship between MTHFR rs1801133 (677C>T) polymorphism and IS risk. However, there have been no definitive conclusions because different populations were examined and inconsistent results were obtained (Herak et al., 2017; Jiménez-González et al., 2021; Huang et al., 2022). Two meta-analyses were performed separately in 2016 and 2019 that reported a correlation between MTHFR rs1801133 (677C>T) polymorphism and IS (Song et al., 2016; Chang et al., 2019). However, only 22 studies were included in Song et al. (2016). Since then, many studies have been conducted in different populations. Moreover, the meta-analysis by Song et al. focused on the general population and did not consider whether MTHFR rs1801133 (677C>T) polymorphism might have varying effects on the risk of IS in different populations. Furthermore, Guilin Chang et al.‘s study, published in 2019, included only nine studies on the elderly population and did not consider young and middle-aged IS patients (Chang et al., 2019). Therefore, past meta-analyses were updated to investigate whether MTHFR rs1801133 (677C>T) polymorphism and stroke risk are related across age and ancestry groups in this study.
2 Materials and methods
The study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (Moher et al., 2009).
2.1 Literature search
A systematic search of the PubMed, EMBASE, Cochrane Library, Web of Science, and CNKI databases for relevant observational studies published until 15 March, 2022, was undertaken independently by two reviewers (Zhao and Li). We used the following search terms to identify eligible studies: (“methylenetetrahydrofolate reductase” OR “MTHFR” OR “C677T” OR “rs1801133”), (“ischemic stroke” OR “cerebral infarction” OR “stroke”), AND (“single nucleotide polymorphism” OR “SNP” OR “genetic polymorphism” OR “mutation” OR “variation”). We reviewed the full text of each study when abstracts and titles were insufficient to make a final determination regarding study inclusion. The reference lists of included studies and existing reviews were screened to identify additional eligible studies. Any disagreements in the study selection process were resolved by a third person (Dang).
2.2 Selection criteria
We included the studies according to the following inclusion criteria: 1) the full text could be searched in electronic databases; 2) the studies were case-control or cohort studies examining MTHFR rs1801133 (677C>T) and stroke susceptibility; 3) the study population was limited to patients diagnosed with stroke for the first time; 4) the MTHFR rs1801133 (677C>T) genotype frequency was provided; and 5) articles were published in English or Chinese. The main exclusion criteria included the following: 1) the studies were duplicate articles or non-original research (letters, commentaries, editorials, reviews, and meta-analyses); 2) the studies were case reports or involved animal experiments; 3) the genotype frequency of MTHFR rs1801133 (677C>T) was not provided; and 4) the p-value of the Hardy–Weinberg equilibrium (HWE) test was <0.05.
2.3 Data extraction and quality assessment
A pre-designed extraction form was used to extract the data. The extracted data included the name of the first author, type of stroke, publication date, ancestry groups, sample size (case and control), study design, mean or median age of the population, HWE, and the Newcastle–Ottawa scale score. Disagreements regarding data extraction were resolved by discussions among the two investigators (Zhao and Li), and a third reviewer (Dang) was consulted if necessary. The HWE p-value was also calculated using the genotypic frequencies of MTHFR polymorphisms, and the threshold of HWE deviation was set at 0.05. The quality of eligible publications was assessed using the Newcastle–Ottawa scale (Stang, 2010), and studies with a score of 7–9 were considered to be of good quality.
2.4 Statistical analysis
We used five genetic comparison models, the T allelic model (T vs. C), dominant model (TT + TC vs. CC), recessive model (TT vs. CC + TC), heterozygous model (TC vs. CC), and homozygous model (TT vs. CC), to estimate the relationship between MTHFR rs1801133 (677C>T) polymorphism and stroke susceptibility by calculating the odds ratio (OR) and 95% confidence interval (CI). The I2 statistic was used to evaluate heterogeneity among genetic comparison models, and the pooled OR was estimated via the Mantel-Haenszel random effect model. Heterogeneity between studies is indicated by an I2 > 50%. Moreover, the Bonferroni method was utilized to adjust for multiple comparisons to control the false positive error rate. As we performed multiple comparisons in this meta-analysis for 45 times, the p-value which was less than 0.05/50 (0.001) indicated statistical significance after Bonferroni correction. To determine the possible causes of heterogeneity, the ancestry groups (Asian, European, African, Hispanic, or Latin American (HLA), and other and not reported ancestries (ONR)) and the study population (young: <18 years; middle-aged: 18–60 years; elderly: >60 years) were analyzed in subgroups. In addition, we examined the impact of a single study on the pooled OR by performing sensitivity analyses on different genetic comparison models. Egger’s test, Begg’s test, and funnel plots were used to evaluate the potential publication bias in our study (Peters et al., 2006). Stata 17.0 was used to perform the statistical analysis of all genetic comparison models.
3 Results
3.1 Literature search and characteristics of the included studies
There were 1,925 articles initially identified after searching the databases. Among them, 692 articles were removed because of duplication, and 911 articles were removed after the titles and abstracts were screened. In total, 322 articles were further screened for eligibility by reviewing their full texts, and eventually, 96 articles that met the criteria were selected (Figure 2).
FIGURE 2
Of the 96 studies included, 95 were case-control studies, and one was a nested case-referent study. In total, 52 studies were conducted in the Asian population, 19 were in the European population, 1 was in the African population, 3 were in the Hispanic or Latin American population, and 21 were in other and not reported ancestry population. In total, 14 studies examined children, 27 examined middle-aged people, and 42 examined the elderly population. The other 13 studies examined the general population. The main features of the included studies are shown in Table 1.
TABLE 1
| Author | Year | Disease | Ancestry | Case | Control | Age | Design | HWE | NOS | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CC | CT | TT | CC | CT | TT | ||||||||
| Huang et al., (2022) | 2022 | IS | Asian | 94 | 72 | 32 | 101 | 62 | 5 | >18 | Case-control | 0.21 | 8 |
| Salomi et al., (2021) | 2021 | IS | Asian | 69 | 32 | 4 | 171 | 40 | 4 | 32.7±7.7 | Case-control | 0.36 | 8 |
| Cernera et al., (2021) | 2021 | IS | European | 64 | 140 | 76 | 138 | 206 | 85 | 8 | Case-control | 0.61 | 7 |
| Jiménez-González et al., (2021) | 2021 | IS | HLA | 35 | 105 | 38 | 60 | 83 | 40 | 34.1±5.4 | Case-control | 0.27 | 8 |
| Mazdeh et al., (2021) | 2021 | IS | ONR | 157 | 124 | 37 | 219 | 155 | 26 | 48±0.10 | Case-control | 0.84 | 7 |
| Hou et al., (2018) | 2018 | IS | Asian | 1063 | 793 | 138 | 1427 | 988 | 150 | 68.6±12.1 | Case-control | 0.22 | 9 |
| Mao and Han, (2018) | 2018 | IS | Asian | 73 | 189 | 27 | 82 | 100 | 16 | 68.42±13.26 | Case-control | 0.06 | 8 |
| Li et al., (2017) | 2017 | IS | Asian | 71 | 134 | 95 | 106 | 110 | 45 | 64.2±13.2 | Case-control | 0.08 | 8 |
| Kamberi et al., (2016) | 2017 | IS | European | 15 | 21 | 3 | 27 | 55 | 20 | 2.83–12.59 | Case-control | 0.40 | 8 |
| Ma et al., (2017) | 2017 | IS | Asian | 36 | 106 | 94 | 88 | 183 | 119 | Media 66.0 | Case-control | 0.27 | 7 |
| Lu et al., (2017) | 2017 | IS | Asian | 31 | 97 | 89 | 41 | 109 | 73 | NA | Case-control | 0.8 | 7 |
| Jiang et al., (2017) | 2017 | IS | Asian | 36 | 52 | 18 | 40 | 54 | 12 | 57.8±10.7 | Case-control | 0.33 | 8 |
| Kumar et al., (2016) | 2016 | IS | Asian | 161 | 84 | 5 | 183 | 65 | 2 | 52.83±12.5 | Case-control | 0.14 | 7 |
| Vijayan et al., (2016) | 2016 | IS | Asian | 164 | 35 | 1 | 185 | 8 | 0 | 57.74±13.84 | Case-control | 0.77 | 8 |
| Zhang et al., (2016) | 2016 | IS | Asian | 13 | 27 | 10 | 36 | 18 | 5 | NA | Case-Control | 0.23 | 8 |
| Herak et al., (2017) | 2017 | IS | European | 29 | 34 | 10 | 41 | 51 | 8 | 4.3(0.01–16.7) | Case-control | 0.15 | 7 |
| Ranellou et al., (2015) | 2015 | IS | European | 16 | 28 | 7 | 26 | 36 | 8 | 37.3±8.0 | Case-control | 0.40 | 8 |
| Wei et al., (2015) | 2015 | IS | Asian | 177 | 98 | 26 | 226 | 65 | 6 | 52.6±68.8 | Case-control | 0.60 | 8 |
| Luo et al., (2015) | 2015 | IS | Asian | 55 | 269 | 388 | 52 | 299 | 423 | 65.2±13.9 | Case-control | 0.93 | 8 |
| Lv et al., (2015) | 2015 | IS | Asian | 70 | 98 | 31 | 88 | 116 | 37 | 68.78 ± 10.63 | Case-control | 0.90 | 8 |
| Zhou et al., (2014) | 2014 | IS | Asian | 160 | 270 | 112 | 242 | 308 | 104 | Media 66 | Case-control | 0.72 | 8 |
| Atadzhanov et al., (2013) | 2014 | IS | African | 15 | 8 | 0 | 96 | 20 | 0 | 54 ± 16 | Case-control | 0.31 | 8 |
| Shi, (2014) | 2014 | IS | Asian | 18 | 36 | 31 | 33 | 35 | 14 | 77.89 ± 8.85 | Case-control | 0.38 | 8 |
| Supanc et al., (2014) | 2014 | IS | European | 41 | 78 | 36 | 75 | 59 | 16 | Middle-aged | Case-control | 0.40 | 8 |
| Fekih-Mrissa et al., (2013) | 2013 | IS | ONR | 35 | 43 | 6 | 60 | 35 | 5 | 56.06 ± 12.5 | Case-control | 0.97 | 8 |
| Zhang and Guo, (2012) | 2012 | IS | Asian | 9 | 19 | 12 | 10 | 20 | 10 | 39.25 ± 4.08 | Case-control | 1.00 | 8 |
| Djordjevic et al., (2012) | 2012 | IS | ONR | 24 | 50 | 6 | 33 | 54 | 13 | 6.7 ± 4.9 | Case-control | 0.21 | 8 |
| Djordjevic et al., (2012) | 2012 | IS | ONR | 39 | 23 | 11 | 59 | 47 | 14 | 40.3 ± 11.6 | Case-control | 0.33 | 88 |
| Somarajan et al., (2011) | 2011 | IS | Asian | 137 | 65 | 5 | 129 | 54 | 5 | 54 ± 15.9 | Case-control | 0.82 | 8 |
| Mohamed et al., (2011) | 2011 | IS | Asian | 69 | 60 | 21 | 85 | 48 | 9 | 61.0 ± 10.1 | Case-control | 0.53 | 8 |
| Hultdin et al., (2011) | 2011 | IS | ONR | 172 | 114 | 27 | 401 | 306 | 59 | 55.0 ± 8.0 | Nested | 0.95 | 8 |
| Salem-Berrabah et al., (2010) | 2011 | IS | ONR | 33 | 15 | 2 | 57 | 35 | 5 | Mean 57.62 | Case-control | 0.90 | 7 |
| Isordia-Salas et al., (2010) | 2010 | IS | HLA | 35 | 105 | 38 | 60 | 83 | 40 | 33.1 ± 5.8 | Case-control | 0.27 | 8 |
| Giusti et al., (2010) | 2010 | IS | European | 130 | 240 | 131 | 572 | 529 | 110 | Media 44.0 | Case-control | 0.437 | 7 |
| Tatarskyy et al., (2010) | 2010 | IS | ONR | 73 | 87 | 23 | 50 | 45 | 5 | 64.6 ± 9.1 | Case-control | 0.20 | 8 |
| Al-Allawi et al., (2009) | 2009 | IS | ONR | 26 | 30 | 14 | 27 | 20 | 3 | Media 60 | Case-control | 0.78 | 7 |
| Sun et al., (2009) | 2009 | IS | Asian | 45 | 36 | 38 | 49 | 37 | 10 | >60 | Case-control | 0.45 | 7 |
| Sabino et al., (2009) | 2009 | IS | HLA | 12 | 9 | 0 | 24 | 12 | 1 | 33.3 ± 16.3 | Case-control | 0.73 | 7 |
| Biswas et al., (2009) | 2009 | IS | Asian | 24 | 32 | 2 | 48 | 10 | 0 | <15 | Case-control | 0.47 | 7 |
| Biswas et al., (2009)) | 2009 | IS | Asian | 67 | 49 | 4 | 90 | 30 | 0 | Young | Case-control | 0.12 | 8 |
| (Morita et al., 2009) | 2009 | IS | European | 5 | 6 | 4 | 48 | 37 | 5 | Children | Case-control | 0.53 | 7 |
| Herak et al., (2009) | 2009 | IS | European | 11 | 17 | 5 | 46 | 56 | 10 | Children | Case-control | 0.22 | 7 |
| Goracy et al., (2009) | 2009 | IS | European | 65 | 69 | 18 | 83 | 46 | 6 | 66.7 ± 12.5 | Case-control | 0.91 | 8 |
| Zak et al., (2009) | 2009 | IS | European | 25 | 30 | 9 | 32 | 25 | 2 | Children | Case-control | 0.27 | 8 |
| Djordjevic et al., (2009) | 2009 | IS | ONR | 9 | 16 | 1 | 23 | 22 | 5 | Children | Case-control | 0.94 | 8 |
| Almawi et al., (2009) | 2009 | IS | ONR | 54 | 26 | 38 | 90 | 26 | 4 | NA | Case-control | 0.23 | 7 |
| Sawula et al., (2009) | 2009 | IS | European | 70 | 50 | 8 | 35 | 19 | 5 | 18–101 | Case-control | 0.31 | 8 |
| Yue et al., (2010) | 2009 | IS | Asian | 8 | 19 | 35 | 14 | 11 | 5 | 67 ± 9 | Case-control | 0.29 | 8 |
| Celiker et al., (2009) | 2009 | IS | ONR | 158 | 4 | 0 | 63 | 37 | 6 | Mean 69.8 | Case-control | 0.85 | 8 |
| Shi et al., (2008) | 2008 | IS | Asian | 23 | 45 | 29 | 20 | 45 | 34 | Young | Case-control | 0.07 | 8 |
| Moe et al., (2008) | 2008 | IS | Asian | 73 | 36 | 11 | 136 | 68 | 3 | 62.5 ± 1.1 | Case-control | 0.09 | 8 |
| Gao et al., (2008) | 2008 | IS | Asian | 4 | 20 | 18 | 6 | 11 | 13 | ≤45 | Case-control | 0.22 | 8 |
| Zhang et al., (2008) | 2008 | IS | Asian | 49 | 116 | 80 | 74 | 140 | 68 | 63.7 ± 10.4 | Case-control | 0.91 | 8 |
| Berge et al., (2007) | 2007 | IS | European | 29 | 125 | 182 | 25 | 141 | 163 | Old | Case-control | 0.47 | 7 |
| Nan et al., (2007) | 2007 | IS | Asian | 14 | 55 | 31 | 28 | 53 | 19 | <45 | case-control | 0.49 | 8 |
| Kim et al., (2007) | 2007 | IS | Asian | 81 | 113 | 43 | 66 | 119 | 38 | 61.18 ± 11.09 | Case-control | 0.21 | 8 |
| Komitopoulou et al., (2006) | 2006 | IS | European | 36 | 46 | 8 | 46 | 39 | 18 | 5.55 ± 0.48 | Case-control | 0.06 | 8 |
| Sazci et al., (2006) | 2006 | IS | ONR | 42 | 41 | 9 | 115 | 119 | 25 | 53.45 ± 9.21 | Case-control | 0.47 | 8 |
| Li et al., (2006) | 2006 | IS | Asian | 235 | 184 | 35 | 190 | 128 | 16 | 65.20 ± 12.75 | Case-control | 0.34 | 8 |
| Dikmen et al., (2006) | 2006 | IS | ONR | 75 | 57 | 14 | 32 | 21 | 2 | 63.4 ± 0.87 | Case-control | 0.52 | 8 |
| Gao et al., (2006) | 2006 | IS | Asian | 30 | 49 | 21 | 32 | 44 | 24 | 61.08 ± 10.77 | Case-control | 0.25 | 8 |
| Yanqun et al., (2006) | 2006 | IS | Asian | 49 | 73 | 40 | 49 | 41 | 10 | 55 ± 6 | Case-control | 0.74 | 7 |
| Hermans et al., (2006) | 2006 | IS | ONR | 4 | 13 | 6 | 62 | 58 | 22 | 71.7 ± 9.3 | Case-control | 0.18 | 9 |
| Pezzini et al., (2005) | 2005 | IS | European | 46 | 83 | 34 | 60 | 75 | 23 | 35.0 ± 7.5 | Case-control | 0.96 | 9 |
| En et al., (2005) | 2005 | IS | Asian | 88 | 43 | 5 | 51 | 17 | 2 | 65 ± 10 | Case-control | 0.69 | 8 |
| Yan et al., (2006) | 2005 | IS | Asian | 34 | 24 | 3 | 37 | 17 | 3 | Old | Case-control | 0.58 | 8 |
| Jinhuan et al., (2005) | 2005 | IS | Asian | 55 | 28 | 4 | 53 | 24 | 3 | Mean 65 | Case-control | 0.89 | 8 |
| Alluri et al., (2005) | 2005 | IS | ONR | 47 | 21 | 1 | 48 | 1 | 0 | 7–78 | Case-control | 0.94 | 8 |
| Kawamoto et al., (2005) | 2005 | IS | Asian | 33 | 43 | 21 | 91 | 110 | 40 | 78 ± 8.3 | Case-control | 0.49 | 8 |
| Yi et al., (2005) | 2005 | IS | Asian | 27 | 42 | 9 | 22 | 25 | 3 | 68.3 ± 7.6 | Case-control | 0.23 | 8 |
| Lingling et al., (2004) | 2004 | IS | Asian | 26 | 18 | 3 | 12 | 15 | 5 | 67.16 ± 10.11 | Case-control | 0.93 | 8 |
| Choi et al., (2003) | 2003 | IS | Asian | 62 | 97 | 36 | 73 | 100 | 25 | 61.4 ± 10.9 | Case-control | 0.30 | 7 |
| Jin et al., (2004) | 2003 | IS | Asian | 21 | 59 | 14 | 40 | 49 | 11 | 69.68 ± 8.9 | Case-control | 0.48 | 8 |
| Jin et al., (2004) | 2003 | IS | Asian | 15 | 23 | 21 | 15 | 11 | 7 | NA | Case-control | 0.09 | 7 |
| Yan et al., (2003) | 2003 | IS | Asian | 55 | 28 | 4 | 53 | 24 | 3 | 66.13 ± 12.54 | Case-control | 0.89 | 8 |
| Li et al., (2002) | 2002 | IS | Asian | 58 | 65 | 20 | 97 | 49 | 8 | 40–90 | Case-control | 0.58 | 8 |
| Chuanqing et al., (2002) | 2002 | IS | Asian | 24 | 35 | 10 | 25 | 35 | 7 | 62.3 ± 12.9 | Case-control | 0.30 | 8 |
| Wenping et al., (2003) | 2002 | IS | Asian | 8 | 34 | 19 | 25 | 46 | 15 | 61–79 | Case-control | 0.43 | 8 |
| Huang et al., (2002) | 2002 | IS | Asian | 11 | 25 | 13 | 16 | 24 | 10 | 55.5 ± 13.0 | Case-control | 0.85 | 8 |
| Guangsen and Chongwen, (2002) | 2002 | IS | Asian | 40 | 47 | 15 | 37 | 47 | 16 | 65 | Case-control | 0.87 | 8 |
| Akar et al., (2001) | 2001 | IS | ONR | 24 | 18 | 4 | 39 | 23 | 6 | Children | Case-control | 0.34 | 7 |
| Wu et al., (2001) | 2001 | IS | Asian | 23 | 40 | 14 | 92 | 113 | 24 | 61.4 ± 6.8 | Case-control | 0.21 | 8 |
| Yaqin et al., (2001) | 2000 | IS | Asian | 15 | 23 | 21 | 15 | 11 | 7 | NA | Case-control | 0.09 | 7 |
| Zheng et al., (2000) | 2000 | IS | Asian | 43 | 62 | 10 | 62 | 45 | 15 | Mean 59 | Case-control | 0.14 | 8 |
| Cumming et al., (1999) | 1999 | IS | ONR | 41 | 6 | 1 | 42 | 6 | 0 | 7–36 | Case-control | 0.64 | 7 |
| Harmon et al., (1999) | 1999 | IS | European | 74 | 73 | 27 | 86 | 78 | 19 | >60 | Case-control | 0.83 | 7 |
| Gaustadnes et al., (1999) | 1999 | IS | European | 97 | 88 | 22 | 545 | 449 | 90 | 25–68 | Case-control | 0.85 | 8 |
| Akar et al., (1999) | 1999 | IS | ONR | 14 | 10 | 4 | 63 | 37 | 6 | Children | Case-control | 0.85 | 8 |
| Press et al., (1999) | 1999 | IS | ONR | 72 | 85 | 10 | 50 | 57 | 8 | 65 ± 8 | Case-control | 0.12 | 8 |
| Lalouschek et al., (1999) | 1999 | IS | ONR | 35 | 37 | 9 | 32 | 40 | 9 | 64.76 ± 13.2 | Case-control | 0.50 | 8 |
| Xinliang et al., (1999) | 1999 | IS | Asian | 10 | 45 | 25 | 58 | 32 | 20 | 60.2 ± 6.1 | Case-control | 0.48 | 8 |
| De Stefano et al., (1998) | 1998 | IS | European | 28 | 27 | 17 | 65 | 98 | 35 | Mean 33.9 | Case-control | 0.85 | 8 |
| Kostulas et al., (1998) | 1998 | IS | ONR | 50 | 40 | 10 | 50 | 40 | 10 | NA | Case-control | 0.63 | 7 |
| Salooja et al., (1998) | 1998 | IS | European | 81 | 76 | 16 | 114 | 107 | 21 | 68 (22–94) | Case-control | 0.56 | 8 |
| Nakata et al., (1998) | 1998 | IS | Asian | 19 | 23 | 6 | 35 | 51 | 19 | 30–80 | Case-control | 0.96 | 8 |
| Markus et al., (1997) | 1997 | IS | European | 162 | 146 | 37 | 76 | 63 | 22 | 65.7 (10.5) | Case-control | 0.13 | 7 |
Characteristics of studies included in the meta-analysis.
3.2 Meta-analysis results
There were 34,814 participants (15,569 cases and 19,245 controls) in the 96 studies included in the meta-analysis.
3.2.1 Dominant model
The TT + CT genotype showed significant heterogeneity compared with the CC genotype in the dominant genetic model (I2 = 69.9%; p < 0.001) (Table 2). The MTHFR rs1801133 (677C>T) mutation significantly increased the IS risk under the dominant genetic model (OR = 1.47; 95%CI = 1.33–1.61; p < 0.001). In the ancestry subgroup analysis, the rs1801133 (677C>T) polymorphism of MTHFR was evidently linked to an increased risk of IS in Asian (OR = 1.59; 95%CI = 1.41–1.80; p < 0.001) and Hispanic or Latin population (OR = 1.93; 95%CI = 1.39–2.67; p < 0.001). MTHFR rs1801133 (677C>T) gene polymorphism was associated with IS susceptibility in all age groups except young populations (middle-aged: OR = 1.59, 95%CI = 1.33–1.90, and p < 0.001; elderly: OR = 1.34, 95%CI = 1.17–1.53, and p < 0.001).
TABLE 2
| Model | OR (95% CI) | PZ | I2 | PH |
|---|---|---|---|---|
| Dominant | ||||
| All IS | 1.47 (1.33–1.61) | <0.001a | 69.9% | <0.001 |
| Ancestry | ||||
| Asian | 1.59 (1.41–1.80) | <0.001a | 67.2% | <0.001 |
| European | 1.35 (1.10–1.65) | 0.004 | 69.9% | <0.001 |
| African | 2.56 (0.96–6.85) | 0.061 | — | — |
| Hispanic or Latin American | 1.93 (1.39–2.67) | <0.001a | 0.0% | 0.824 |
| Other and not reported ancestries | 1.20 (0.91–1.57) | 0.190 | 76.4% | <0.001 |
| Age | ||||
| Young | 1.46 (1.12–1.91) | 0.005 | 52.2% | 0.012 |
| Middle-aged | 1.59 (1.33–1.90) | <0.001a | 69.8% | <0.001 |
| Elderly | 1.34 (1.17–1.53) | <0.001a | 71.3% | <0.001 |
| NA | 1.77 (1.30–2.41) | <0.001a | 69.3% | <0.001 |
Pooled odds ratios (ORs) and 95% confidence intervals (CIs) of the association between C677T polymorphism and stroke in the dominant model.
Bonferroni correction for multiple testing was applied (p-value threshold, 0.001);
PZ, p-value for the Z-test; PH, p-value for heterogeneity;
Association was still significant after Bonferroni correction for multiple testing.
3.2.2 Recessive model
The TT genotype showed significant heterogeneity compared with the CC + CT genotype in the recessive genetic model (I2 = 55.7%; p < 0.001) (Table 3). MTHFR rs1801133 (677C>T) polymorphism was associated with an increased risk of stroke under the recessive model (OR = 1.52; 95%CI = 1.36–1.71; p < 0.001). The ancestry subgroup analysis showed a significant difference in the Asian populations, with combined ORs of 1.58 (95% CI = 1.38–1.81; p < 0.001). The middle-aged and elderly people had an increased risk of stroke according to the subgroup analysis (middle-aged: OR = 1.55, 95%CI = 1.22–1.96, and p < 0.001; elderly: OR = 1.47, 95%CI = 1.28–1.68, and p < 0.001)
TABLE 3
| Model | Or (95% CI) | PZ | I2 | PH |
|---|---|---|---|---|
| Recessive | ||||
| All IS | 1.52 (1.36–1.71) | <0.001a | 55.7% | <0.001 |
| Ancestry | ||||
| Asian | 1.58 (1.38–1.81) | <0.001a | 47.1% | <0.001 |
| European | 1.48 (1.11–1.97) | 0.007 | 73.1% | <0.001 |
| African | — | — | — | — |
| Hispanic or Latin American | 0.96 (0.68–1.37) | 0.839 | 0.0% | 0.949 |
| Other and not reported ancestries | 1.47 (1.05–2.05) | 0.026 | 49.6% | 0.005 |
| Age | ||||
| Young | 1.25 (0.81–1.92) | 0.313 | 53.7% | 0.009 |
| Middle-aged | 1.55 (1.22–1.96) | <0.001a | 57.5% | <0.001 |
| Elderly | 1.47 (1.28–1.68) | <0.001a | 46.8% | 0.001 |
| NA | 1.99 (1.29–3.07) | <0.001a | 64.7% | 0.001 |
Pooled odds ratios (ORs) and 95% confidence intervals (CIs) of the association between C677T polymorphism and stroke in the recessive model.
Bonferroni correction for multiple testing was applied (p-value threshold 0.001);
PZ, p-value for the Z-test; PH, p-value for heterogeneity;
Association was still significant after Bonferroni correction for multiple testing.
3.2.3 Heterozygous model
The TC genotype showed significant heterogeneity compared with the CC genotype in the heterozygous genetic model (I2 = 60.4%; p < 0.001) (Table 4). There was an obvious association between MTHFR rs1801133 (677C>T) polymorphism and increased risk of stroke under the heterozygous model (OR = 1.36; 95%CI = 1.24–1.48; p < 0.001). In the subgroup analysis, MTHFR rs1801133 (677C>T) gene polymorphism was associated with stroke susceptibility in Asian (OR = 1.46; 95%CI = 1.30–1.63; p < 0.001), Hispanic or Latin populations (OR = 2.09; 95%CI = 1.50–2.95; p < 0.001), middle-aged (OR = 1.50; 95%CI = 1.27–1.78; p < 0.001), and elderly groups (OR = 1.23; 95%CI = 1.08–1.40; p = 0.001).
TABLE 4
| Model | OR (95% CI) | PZ | I2 | PH |
|---|---|---|---|---|
| Heterozygote | ||||
| All IS | 1.36 (1.24–1.48) | <0.001a | 60.4% | <0.001 |
| Ancestry | ||||
| Asian | 1.46 (1.30–1.63) | <0.001a | 58.2% | <0.001 |
| European | 1.27 (1.08–1.51) | 0.005 | 50.4% | 0.006 |
| African | 2.56 (0.96–6.85) | 0.061 | — | — |
| Hispanic or Latin American | 2.09 (1.50–2.95) | <0.001a | 0.0% | 0.825 |
| Other and not reported ancestries | 1.10 (0.86–1.40) | 0.453 | 67.6% | <0.001 |
| Age | ||||
| Young | 1.44 (1.13–1.84) | 0.003 | 38.7% | 0.069 |
| Middle-aged | 1.50 (1.27–1.78) | <0.001a | 62.5% | <0.001 |
| Elder | 1.23 (1.08–1.40) | 0.001a | 62.8% | 0.001 |
| NA | 1.48 (1.14–1.92) | 0.003 | 50.2% | 0.020 |
Pooled odds ratios (ORs) and 95% confidence intervals (CIs) of the association between C677T polymorphism and stroke in the heterozygous model.
Bonferroni correction for multiple testing was applied (p-value threshold 0.001);
PZ, p-value for the Z-test; PH, p-value for heterogeneity;
Association was still significant after Bonferroni correction for multiple testing.
3.2.4 Homozygous model
The TT genotype showed significant heterogeneity compared with the CC genotype in the homozygous genetic model (I2 = 64.2%; p < 0.001) (Table 5). There was also a significant association between MTHFR rs1801133 (677C>T) polymorphism and an increased risk of stroke under this model (OR = 1.82; 95%CI = 1.58–2.11; p < 0.001). However, the stratification analysis results were similar to those of the recessive model. Significant correlation was detected between MTHFR rs1801133 (677C>T) polymorphisms and the increased risk of stroke in the Asian population (OR = 1.98; 95%CI = 1.66–2.37; p < 0.001). Furthermore, the middle-aged and elderly people had an increased risk of stroke in the subgroup analysis (middle-aged: OR = 1.92, 95%CI = 1.45–2.53, and p < 0.001; elderly: OR = 1.74, 95%CI = 1.44–2.11, and p < 0.001).
TABLE 5
| Model | Or (95% CI) | PZ | I2 | PH |
|---|---|---|---|---|
| Homozygote | ||||
| All IS | 1.82 (1.58–2.11) | <0.001a | 64.2% | <0.001 |
| Ancestry | ||||
| Asian | 1.98 (1.66–2.37) | <0.001a | 59.4% | <0.001 |
| European | 1.65 (1.14–2.39) | 0.008 | 79.3% | <0.001 |
| African | — | — | — | — |
| Hispanic or Latin American | 1.60 (1.05–2.46) | 0.030 | 0.0% | 0.863 |
| Other and not reported ancestries | 1.59 (1.09–2.32) | 0.017 | 56.2% | 0.001 |
| Age | ||||
| Young | 1.43 (0.88–2.33) | 0.146 | 55.6% | 0.006 |
| Middle-aged | 1.92 (1.45–2.53) | <0.001a | 62.7% | <0.001 |
| Elder | 1.74 (1.44–2.11) | <0.001a | 62.3% | <0.001 |
| NA | 2.45 (1.47–4.01) | 0.001a | 69.1% | <0.001 |
Pooled odds ratios (ORs) and 95% confidence intervals (CIs) of the association between C677T polymorphism and stroke in the homozygous model.
Bonferroni correction for multiple testing was applied (p-value threshold 0.001);
PZ, p-value for the Z-test; PH, p-value for heterogeneity;
Association was still significant after Bonferroni correction for multiple testing.
3.2.5 Allelic model
The T allele showed significant heterogeneity compared with the C allele in the allelic genetic model (I2 = 75.7%; p < 0.001) (Table 6). There was an obvious association between MTHFR rs1801133 (677C>T) polymorphism and an increased risk of stroke under the allelic model (OR = 1.37; 95%CI = 1.27–1.48; p < 0.001). In the subgroup analysis, MTHFR rs1801133 (677C>T) gene polymorphism was associated with stroke susceptibility in Asian populations (OR = 1.46; 95%CI = 1.33–1.60; p < 0.001). The middle-aged and elderly people with T allele mutation had a higher risk of stroke (middle-aged: OR = 1.42, 95%CI = 1.24–1.64, and p < 0.001; elderly: OR = 1.30, 95%CI = 1.18–1.43, and p < 0.001).
TABLE 6
| Model | Or (95% CI) | PZ | I2 | PH |
|---|---|---|---|---|
| Allele | ||||
| All IS | 1.37 (1.27–1.48) | <0.001a | 75.7% | <0.001 |
| Ancestry | ||||
| Asian | 1.46 (1.33–1.60) | <0.001a | 72.6% | <0.001 |
| European | 1.29 (1.09–1.53) | 0.003 | 79.5% | <0.001 |
| African | 2.51 (1.06–5.93) | 0.036 | — | — |
| Hispanic or Latin American | 1.28 (1.05–1.57) | 0.016 | 0.0% | 0.981 |
| Other and not reported ancestries | 1.26 (0.96–1.52) | 0.116 | 81.4% | <0.001 |
| Age | ||||
| Young | 1.31 (1.05–1.64) | 0.016 | 65.5% | <0.001 |
| Middle-aged | 1.42 (1.24–1.64) | <0.001a | 73.7% | <0.001 |
| Elder | 1.30 (1.18–1.43) | <0.001a | 75.0% | <0.001 |
| NA | 1.70 (1.28–2.26) | <0.001a | 80.6% | <0.001 |
Pooled odds ratios (ORs) and 95% confidence intervals (CIs) of the association between C677T polymorphism and stroke in the allelic model.
Bonferroni correction for multiple testing was applied (p-value threshold 0.001);
PZ, p-value for the Z-test; PHp-value for heterogeneity;
Association was still significant after Bonferroni correction for multiple testing.
3.3 Sensitivity analysis
A sensitivity analysis was conducted to compare the pooled ORs after individually excluding each included study. There was no significant change in the results (Supplementary Figure S1).
3.4 Publication bias
The funnel plot is shown in Figure 3. All research studies included in this study distributed above the funnel plots, which indicated that variability of the effect size was low and the results were reliable. The Egger’s funnel plots for these five models were basically symmetrical though Egger’s test, indicating there was publication bias in the dominant (p = 0.04) and heterozygous models (p = 0.03) (Table 7). Nonetheless, we did not find any publication bias in all genetic models using Begg’s tests. The correlation between the lnOR and its variance and the level of heterogeneity across studies might contribute to the discrepancy between Egger’s and Begg’s tests. Actually, Begg’s test is more robust and has the appropriate type I error rates despite the sample size, the number of included studies, and the level of heterogeneity. Furthermore, when the summary estimates are ORs or RRs and there is obvious heterogeneity between studies (Schwarzer et al., 2002; Peters et al., 2006), type I error rates for Egger’s test are higher than those for Begg’s test.
FIGURE 3
4 Discussion
This meta-analysis demonstrates associations between MTHFR rs1801133 (677C>T) genetic polymorphism and susceptibility to IS under all genetic models. Our results were consistent with a previous meta-analysis performed in 2016, wherein this polymorphism was found to be potentially involved in the development of IS (Song et al., 2016). This suggests the MTHFR C677T mutation is a genetic risk factor of IS, and primary and secondary prevention should be initiated in a timely manner in population with this mutation.
Several factors might explain the association of the MTHFR rs1801133 (677C>T) mutation and increased IS risk. Most importantly, the MTHFR rs1801133 (677C>T) mutation leads to decreased MTHFR activity and elevated homocysteine levels (Castro et al., 2004). Hyperhomocysteinemia is linked to the overproduction of free radicals (Xi et al., 2016), induction of oxidative stress (Esse et al., 2019; Tchantchou et al., 2021), endothelial injury (Salvio et al., 2021), coagulation, and lipid metabolism disturbance (Herrmann, 2001), which all contribute to the incidence of IS. Meanwhile, previous studies demonstrated that people with the MTHFR rs1801133 (677C>T) mutation show a poor response to homocysteine-lowering treatment (Qin et al., 2020). Furthermore, a meta-analysis published in the current year showed that MTHFR rs1801133 (677C>T) polymorphism is related to susceptibility to H-type hypertension (Liao et al., 2022), which is a traditional risk factor for IS.
We also conducted a subgroup analysis on the basis of age and ancestry of the study population to further understand the significance of the MTHFR rs1801133 (677C>T) mutation in various populations. The result of subgroup analysis showed increased IS risk in populations with the MTHFR rs1801133 (677C>T) mutation in middle-aged and elderly groups. It was consistent with the fact that older people were more susceptible to atherosclerosis, which was an important cause of IS. Previous studies had demonstrated that the MTHFR rs1801133 (677C>T) mutation increased the risk of IS in patients with large-artery atherosclerosis (Cui, 2016) and adults (Xin et al., 2009).
Another important finding of this meta-analysis was the stable association between IS risk and MTHFR rs1801133 (677C>T) polymorphism in Asian populations in all genetic models and Hispanic or Latin American population in dominant and heterozygous models. Similar trends were also found among other populations, although no statistically significant difference was found in some genetic models. This may be related to the following reasons: 1) the frequency of the MTHFR 677T gene variant differs among ethnic groups due to different genetic backgrounds. Previous studies indicated that the frequency of the MTHFR rs1801133 T allele was 24–40% in Europeans, 40% in Koreans, and 26–37% in Japanese (Shao et al., 2017); 2) MTHFR rs1801133 (677C>T) was associated with increased coronary heart disease only when the folate level was low (Klerk et al., 2002). Thus, various dietary habits and differences in folate intake may also contribute to this difference; 3) the difference in the power of included studies may be another cause of this result. Nonetheless, the results for these ancestry groups need to be interpreted with caution, and more high-quality studies are still required to explore the correlation between MTHFR rs1801133 (677C>T) polymorphism and IS risk in these ancestry groups.
This study has several strengths. First, we included the most recent and relevant studies in this meta-analysis. In addition, we further analyzed the association between MTHFR rs1801133 (677C>T) polymorphism and IS risk in different populations. Finally, this meta-analysis included high-quality observational studies using real-world data with a large number of patients.
However, this meta-analysis also has some limitations. First, the study was based on the secondary study-level data. Age groups were defined according to the mean or median age of study subjects, and some studies did not provide clear information on age. Thus, the age stratification of subgroups might not be accurate. Second, the findings of this meta-analysis were mainly based on case-control studies and lacked prospective research; therefore, they should be interpreted with caution.
5 Conclusion
Our findings showed that the MTHFR rs1801133 (677C>T) variant may contribute to an increased risk of IS. This association was statistically significant in the Asian and Hispanic or Latin American cohorts and showed a similar trend in the populations of other ancestries. For middle-aged and elderly people, MTHFR rs1801133 (677C>T) might be a promising biomarker for early detection and prediction of the prognosis of IS. However, high-quality, prospective studies are needed in the future.
Statements
Author contributions
All authors contributed to the data analysis and drafting or revision of the manuscript, gave final approval of the version to be published, and agreed to be accountable for all aspects of the work.
Funding
This work was supported by the National Natural Science Foundation of China under the Grant No. 81971116 and the Key Research and Development Program of Shaanxi under the Grant No. 2019ZDLSF01–04.
Acknowledgments
The authors would like to thank all of our teammates for contributing to this work. They also thank Lisa Kreiner, PhD, from Liwen Bianji, (Edanz) (www.liwenbianji.cn/), for editing the English text of a draft of this manuscript.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2022.1021423/full#supplementary-material
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Summary
Keywords
polymorphism, ischemic stroke, meta-analysis, risk, MTHFR rs1801133 (677C>T)
Citation
Zhao L, Li T, Dang M, Li Y, Fan H, Hao Q, Song D, Lu J, Lu Z, Jian Y, Wang H, Wang X, Wu Y and Zhang G (2023) Association of methylenetetrahydrofolate reductase (MTHFR) rs1801133 (677C>T) gene polymorphism with ischemic stroke risk in different populations: An updated meta-analysis. Front. Genet. 13:1021423. doi: 10.3389/fgene.2022.1021423
Received
03 October 2022
Accepted
29 November 2022
Published
04 January 2023
Volume
13 - 2022
Edited by
Lindsay Fernandez-Rhodes, The Pennsylvania State University (PSU), United States
Reviewed by
Shifu Li, Central South University, China
Reza Jabal, Albert Einstein College of Medicine, United States
Updates
Copyright
© 2023 Zhao, Li, Dang, Li, Fan, Hao, Song, Lu, Lu, Jian, Wang, Wang, Wu and Zhang.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Guilian Zhang, zhgl_2006@xjtu.edu.cn
This article was submitted to Applied Genetic Epidemiology, a section of the journal Frontiers in Genetics
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