Unveiling the link: Evaluating MTHFR gene polymorphisms and colorectal cancer risk through meta-analysis

Abstract

Colorectal cancer pathogenesis is a multifactorial process, with genetic factors playing a significant role in cancer development. A review of published meta-analyses on MTHFR gene polymorphisms and colorectal cancer susceptibility showed inconsistent findings and failed to assess the reliability of statistically significant results. Case-control studies were manually searched in databases to investigate the association between MTHFR gene polymorphisms and colorectal cancer. The study assessed the strength of association for the five gene models by calculating odds ratios (ORs) and 95% confidence intervals (CIs). The study results were also analyzed for the source of heterogeneity, sensitivity, publication bias, and false-positive report probability (FPRP) test. Additionally, extensive subgroup analyses were conducted to investigate the impact of confounding factors on the associations. The study suggests that MTHFR C677T gene polymorphism reduces the risk of colorectal cancer in Asian and mixed-race populations, while increasing the risk of Colorectal cancer in the Indian ethnic group. MTHFR A1298C may play a protective role in the development of colorectal cancer. These findings provide valuable insights for the early diagnosis and prevention of Colorectal cancer. However, further studies are required to confirm the association, which may offer additional information for the early diagnosis and prevention of Colorectal cancer.

Introduction

Colorectal cancer (CRC) is a significant threat to human life and health, with the fourth-highest mortality rate and the third-highest incidence rate of all malignant tumors globally [1]. It poses a considerable burden to society [2]. The incidence of colorectal cancer (CRC) has been steadily increasing in recent years. According to the latest data, more than 1.9 million new cases of CRC were reported globally in 2020, with a mortality rate of 50%. This makes CRC the third most common malignant tumour among adults [3]. However, the pathogenesis of CRC remains poorly understood. The pathogenesis of CRC is a complex multifactorial process, as revealed by epidemiological studies. This process involves the interaction of genetic, epigenetic, and environmental factors. Genetic factors, such as single nucleotide polymorphisms (SNPs) in CRC-associated genes, as well as non-genetic factors, such as obesity, physical inactivity, smoking, and alcohol consumption, have been shown to play a significant role in the development of CRC [4,5]. In recent years, research has identified numerous genetic polymorphisms associated with CRC [6]. These SNPs can serve as markers for improving cancer diagnosis and determining therapeutic options [7]. Notably, the role of the folate metabolising enzyme gene - methylenetetrahydrofolate reductase (MTHFR) - in the pathogenesis of colorectal cancer has gained widespread attention among researchers[13].

MTHFR is a crucial enzyme in the folate metabolism pathway. It catalyses the irreversible conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate, which regulates intracellular folate content and DNA methylation [8,9]. MTHFR has several SNPs loci in the clinic, of which C677T (RS1801133) and A1298C (RS1801131) are the two most significant. RS1801133 is located in exon 4 and converts cytosine (C) to thymine (T) at nucleotide 677. This prompts the conversion of alanine to valine at position 222, with three genotypes CC, CT and TT [10]. RS1801131, located in exon 7, drives the conversion of adenine (A) to cytosine (C) at nucleotide 1298, causing a glutamate to alanine mutation with genotypes AA, AC and CC [11]. Mutations in metabolic enzyme genes can interfere with the folate metabolic pathway, leading to folate deficiency. This is significant because folate plays a crucial role in DNA synthesis and biosynthesis of nucleotide precursors for DNA, RNA and protein methylation [12]. Mutations in the MTHFR gene can also cause DNA hypomethylation, resulting in aberrant expression of proto-oncogenes and alterations in gene transcription, which can promote CRC [13].

Numerous studies have demonstrated an association between MTHFR gene polymorphisms and various diseases, including psychiatric disorders, gastric cancer, hepatocellular carcinoma, lung cancer, cervical cancer, hypertension, cerebral infarction, and coronary heart disease [14]. However, the role of MTHFR gene polymorphisms in the pathogenesis of CRC remains inconclusive. This may be due to differences in study design, geography, ethnicity, and dietary habits. After reviewing previous meta-analyses [15–41] and basic studies [17,42–104] that explored the relationship between MTHFR gene polymorphisms and CRC susceptibility, it is evident that the results are still highly controversial. Issues such as delayed updating, inappropriate inclusion of literature, inconsistent quality of reporting, and omission of important literature may have contributed to this situation. Furthermore, prior meta-analyses have failed to evaluate the reliability of statistical associations, potentially resulting in erroneous conclusions. It is worth noting that a number of recent studies have been published [136–140]. Therefore, conducting more comprehensive and detailed meta-analyses based on existing case-control and cohort studies is necessary to clarify the correlation between the MTHFR C677T and A1298C polymorphisms and the risk of CRC. This will provide a population-based reference for CRC risk assessment, prevention, and control.

Materials and methods

Search strategy

The literature search was conducted in databases such as PubMed, Web of Knowledge, ISI, China Knowledge, and Wanfang databases in strict accordance with PRISMA criteria [141]. The search was confirmed by screening titles, abstracts, and reading the complete literature in detail. References to identified meta-analyses and reviews were also checked to ensure no relevant studies were missed. The deadline for the search is October 2023. The search strategy for the English database specifically includes the terms ‘polymorphism’, ‘variant’, ‘variation’, ‘mutation’, ‘SNP’, ‘genome-wide association study’, ‘genetic association study’, ‘genotype’, and ‘allele’, combined with the terms ‘colorectal’, ‘rectal’, ‘colon’, ‘intestine’, and ‘gut’, as well as ‘MTHFR’, ‘Methylenetetrahydrofolate reductase’, and ‘5, 10-Methylenetetrahydrofolate reductase’. The Chinese database was searched using the following subject terms: ‘methylenetetrahydrofolate reductase ‘, ‘gene polymorphism’, ‘colorectal cancer’, ‘rectal cancer’.

Selection criteria

Inclusion criteria: (1) Case-control studies or cohort studies; (2) Correlation studies on the relationship between polymorphisms in the MTHFR C677T (RS1801133) and/or A1298C (RS1801131) genes and susceptibility to colon cancer, rectal cancer, and colorectal cancer; (3) The genotype frequencies corresponding to the genetic polymorphisms in the case and control groups can be obtained from the literature.

Exclusion criteria: (1) Studies with missing or duplicated data; (2) Reviews, letters, and case reports; (3) Studies that included colonic and rectal polyps in the case group; (4) Studies with poorly described data.

Data extraction.

To ensure the accuracy of the extracted information, two authors independently performed the inclusion and exclusion criteria for each study to extract useful information. In case of disagreement, the corresponding author would be responsible for re-extracting the data, which would then be confirmed and validated. Furthermore, when the data was insufficient or uncertain, the original authors were contacted to verify and supplement its accuracy. Studies with incomplete data were excluded, and only the highest quality studies were retained, while repetitive, duplicated, or similar studies were excluded. The provided information was used to complete a standardised table. This included the last name of the first author, year of publication, country, ethnicity (Asian, Caucasian, African, Indian, Mixed), sample size of cases and controls, source of controls (hospital-based or population-based), type of match, site of tumour, and frequency of genotypes in the cases and controls. The details can be found in Table 1.

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Quality assessment

The study used the quality assessment scale based on the Preferred Reporting Entries for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [141], the Guidelines for Reporting the Quality of Observational Studies [142,143], and the Quality Assessment of Prior Meta-Analyses [14]. Two authors independently assessed the quality of each included study. S1 Table provides information on the scores used to evaluate the quality of the studies included in the meta-analyses. The total quality scores ranged from 0-18. Articles with a score of 12 or more were considered high-quality, those with a score of 9-12 were considered moderate-quality, and those with a score less than 9 were considered low-quality.

Statistical analysis

The study calculated the pooled odds ratios (ORs) and corresponding 95% confidence intervals (95%CIs) of gene frequencies for each of the five genetic models to assess the association between MTHFR polymorphisms and the risk of CRC. A statistically significant result was considered when P < 0.05. The five MTHFR C677T genetic models analysed were: (1) allele model T vs C; (2) additive model TT vs CC; (3) dominant model TT + CT vs CC; (4) recessive model TT vs CT + CC; and (5) super-dominant model CT vs CC. The MTHFR A1298C genetic models analysed were: (1) allele model C vs A; (2) additive model CC vs AA; (3) dominant model CC + AC vs AA; (4) recessive model CC vs AC + AA; and (5) super-dominant model AC vs AA.

Hardy-Weinberg equilibrium (HWE) was calculated for each study control group using a goodness-of-fit test. A significant disequilibrium (HWD) was defined as P < 0.05, otherwise, it was defined as HWE [144]. Subgroup analyses were conducted by stratifying studies based on the type of control matching, HWE condition, source of control, ethnicity, gender, tumour site, and TNM stage. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated to demonstrate the strength of this association.The meta-analysis’s heterogeneity was evaluated using the chi-square Q-test and I² test. Results were interpreted as having no significant heterogeneity [145] if P > 0.10 and/or I² ≤ 50%, and a fixed effects model (FEM) [146] was selected. If P < 0.10 and/or I² > 50%, heterogeneity was considered large, and a random effects model (REM) [147] was chosen. To reduce heterogeneity, we used REM [147]. We also conducted subgroup analysis and meta-regression analysis to explore the source of heterogeneity. To assess the stability of the results, we performed sensitivity analyses using three methods: (1) excluding one study at a time; (2) excluding low- or medium-quality studies or those with HWD; and (3) retaining only high-quality and HWE studies. The study considered results to have no significant publication bias when Begg’s funnel plot [148] symmetry and Egger’s test suggested P > 0.05 [149]. In cases where significant publication bias was present, a nonparametric ‘trim and fill’ approach was used to correct and identify funnel plot asymmetries caused by publication bias while estimating the true value of the quantitative synthesis [150]. The False Positive Reporting Probability (FPRP) test [151] and the Venice Criterion [152] were applied to assess the credibility of statistically significant results. All statistical analyses were performed using STATA 12.0 (Stata Corp LP, College Station, Texas).

Results

Description of included studies

Following the established search strategy (refer to Fig 1 for detailed literature search and screening process), a total of 625 articles were obtained. After screening the titles, abstracts, and reading the full text in detail, 100 articles (106 studies) were selected for analysis. The publication year of the selected articles ranged from 1996-2023 [17,42–140]. Out of the selected studies, 104 described the association between the MTHFR C677T polymorphism and CRC susceptibility, while 60 studies described MTHFR A1298C.The analysis included 37 studies on Asians, 50 on Caucasians, 6 on Indians, 4 on Africans, and 7 on mixed-race populations. The quality of the studies was assessed, with 74 being of high quality (score >12) in describing the MTHFR C677T polymorphism and its association with CRC susceptibility. Additionally, there were 23 moderate-quality studies (scores between 9 and 12) and 7 low-quality studies (scores below 9). Regarding studies investigating the association between the MTHFR A1298C polymorphism and CRC risk, there were 43 high-quality studies, 15 moderate-quality studies, and 2 low-quality studies.The genotype distribution in the control groups of all studies, except for 17 [43,44,48,64,69,73,80,83,85,94,111,122,124–126,130,138], was consistent with the HWE test. Table 1 lists the genotype frequencies of the MTHFR C677T and A1298C polymorphisms associated with CRC risk, as well as the results of the HWE test and quality score.Additionally, we gathered genotype frequencies for confounding factors such as tumour type, location, gender, TNM stage, Duke stage, lymph node metastasis, degree of differentiation, smoking, and alcohol consumption. This was done by carefully reviewing the included literature to further investigate the role of these confounding factors in the pathogenic process of MTHFR gene polymorphisms in CRC. Subgroup analyses are detailed in Tables 2 and 3.

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Meta-analysis results

Pooled analysis for MTHFR C677T (rs1801133)

This meta-analysis included 104 case-control studies (41,884 cases and 58,362 controls) that investigated the association between MTHFR C677T and CRC susceptibility. Table 4 shows that two genetic models demonstrated a decreased risk of colorectal cancer due to MTHFR when compared to controls: TT vs CC (OR=0.888, 95% CI=0.822-0.959) and TT vs CC+CT (OR=0.891, 95% CI=0.831-0.956).In the subgroup analyses based on ethnicity, it was observed that the MTHFR C677T gene polymorphism was found to be a susceptibility factor for CRC in Indian ethnic groups(CT+TT vs CC: OR=1.329, 95%CI=1.033-1.709 (FEM); T vs C: OR=1.336,95%CI=1.065-1.675 (FEM)), while significantly reducing the risk of CRC in Asian and mixed races(Asian TT vs CC: OR=0.783, 95%CI=0.669-0.917; TT vs CC+CT: OR=0.811, 95%CI=0.708-0.929; T vs C: OR=0.906, 95%CI=0.836-0.981; mixed race TT vs CC: OR=0.831, 95%CI=0.746-0.926 (FEM); TT vs CC+CT: OR=0.824, 95%CI=0.743-0.914 (FEM); T vs C: OR=0.946, 95%CI=0.902- 0.993 (FEM)).It has been observed that there are negative correlations between MTHFR gene polymorphisms and susceptibility to CRC in both population-based control groups and control groups from non-cancer studies.(PB：TT vs CC: OR=0.850, 95%CI=0.804-0.898 (FEM); TT vs CC+CT: OR=0.845, 95%CI=0.802-0.890 (FEM); T vs C: OR=0.954, 95%CI= 0.931-0.978 (FEM);Non-cancer controls:TT vs CC: OR=0.834, 95%CI=0.792-0.877 (FEM); TT vs CC+CT: OR=0.834, 95%CI=0.795-0.875 (FEM)). Table 4 and Fig 2 show the results of the pooled analyses and racial distribution.

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TT vs. CC (overall data).

Table 5 presents the details of an extensive subgroup analysis that was conducted to further investigate the association between the MTHFR C677T polymorphism and susceptibility to CRC. In subgroup analyses based on tumour site, it was observed that MTHFR gene polymorphisms were associated with a reduced risk of colon cancer only in the TT vs. CC+CT model (OR=0.833, 95%CI=0.698-0.994). But no significant association was found between MTHFR gene polymorphisms and rectal cancer susceptibility. The results of the stratified analysis indicate that a low degree of differentiation is significantly associated with a reduced risk of CRC (TT vs CC: OR=0.592, 95%CI=0.380-0.923 (FEM)). However, no association was found in all genetic models for the highly and moderately differentiated studies. On the other hand, the genetic models for non-mucinous carcinoma studies suggest that MTHFR polymorphisms may act as protective factors(TT vs CC: OR=0.503, 95%CI=0.281-0.899; CT vs CC: OR=0.775,95%CI=0.627-0.958 (FEM); TT vs CC+CT: OR=0.509, 95%CI=0.377-0.687 (FEM); CT+TT vs CC: OR=0.685, 95%CI=0.561-0.838 (FEM); T vs C. OR=0.729,95%CI=0.552-0.964). In contrast, there is no association between mucinous colorectal cancer susceptibility and MTHFR polymorphisms. Of note, in the subgroup analysis based on tumour location, it was observed that MTHFR polymorphisms were identified as a risk factor for proximal CRC (CT vs CC: OR=1.251,95%CI=1.003-1.560) and a protective factor for distal CRC(TT vs CC: OR=0.853, 95%CI=0.729-0.997 (FEM)). In the analysis stratified by Dukes staging, it was observed that MTHFR reduced susceptibility to stage A and C CRC (stage A CRC:TT vs CC: OR=0.434, 95%CI=0.234-0.808 (FEM); TT vs CC+CT: OR=0.505, 95%CI=0.282-0.907 (FEM);stage C CRC:TT vs CC: OR=0.601, 95%CI=0.428-0.844 (FEM); TT vs CC+CT: OR=0.646, 95%CI=0.468-0.892 (FEM); T vs C: OR=0.821,95%CI=0.712-0.945 (FEM)), but not in relation to Stage B and D CRC. Similar results were observed in both drinking and non-drinking studies when analyses were stratified according to alcohol consumption. Additionally, subgroup analyses were performed according to gender, TNM stage and lymph node metastasis, and smoking status, and no associations were observed.

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Pooled analysis for MTHFR A1298C (rs1801131)

Table 6 and Fig 3 present the results of pooled analyses of the MTHFR A1298C polymorphism and CRC susceptibility, including ethnic distribution. In the meta-analysis, a total of 60 case-control studies were included, comprising of 18,103 cases and 26,970 controls. It was observed that none of the genetic models showed any statistically significant associations. The subgroup analyses based on ethnicity and type of control also yielded similar results. Nevertheless, in population-based control studies, three genetic models suggest that the MTHFR C677T polymorphism is associated with a reduced risk of CRC (CC vs AA: OR=0.895,95% CI=0.822-0.976 (FEM); CC vs AA+AC: OR=0.900,95% CI=0.829-0.977 (FEM); C vs A: OR =0.961, 95% CI=0.926-0.998 (FEM)).

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CC vs. AA (overall data).

Table 7 shows the results of subgroup analyses of MTHFR A1298C polymorphisms and CRC risk. It is worth noting that three genetic models (CC vs AA: OR =0.729, 95%CI=0.582-0.913(FEM); CC vs AA+AC: OR =0.751, 95%CI=0.604-0.933(FEM); and C vs A: OR =0.905, 95%CI =0.833-0.984 (FEM)) suggest that MTHFR A1298C reduces susceptibility in patients with rectal cancer, but in the colon cancer study only the recessive model showed similar results (CC vs AA+AC: OR =0.850, 95%CI =0.729-0.992 (FEM)). Moreover, the study did not find any statistical associations in stratified analyses based on gender, degree of differentiation, and tumour site. However, it should be noted that in subgroup analyses based on Dukes staging, the MTHFR A1298C polymorphism emerged as a susceptibility factor for stage A+B CRC (AC vs AA:OR=1.445,95%CI=1.059-1.972 (FEM)), while no statistical association could be found for stage C+D CRC. In the stratified analyses based on alcohol consumption, it was observed that both drinking and non-drinking subgroups demonstrated that MTHFR A1298C had a protective effect against CRC (non-drinking: CC vs. AA: OR =0.579, 95%CI=0.347-0.967 (FEM); CC vs. AA+AC: OR =0.610, 95%CI =0.376-0.989 (FEM). AC+CC vs. AA: OR =0.725, 95%CI =0.546-0.963 (FEM); C vs A: OR =0.311, 95%CI =0.189-0.512 (FEM); Drinking: CC vs AA: OR =0.249, 95%CI=0.087-0.711 (FEM); CC vs AA+ AC: OR =0.388, 95%CI =0.152-0.993 (FEM); C vs A: OR =0.744, 95%CI =0.623-0.889 (FEM)).

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Heterogeneity and sensitivity analyses

Meta-regression analyses were conducted to investigate potential sources of heterogeneity in the overall and subgroup analyses. The sources of heterogeneity for MTHFR C677T were race (TT vs.CC:P = 0.004;CT+TT vs.CC: P = 0.012; TT vs. CC+CT: P = 0.010; T vs. C: P = 0.002), type of control (TT vs. CC+CT: P = 0.032), and HWE (T vs. C: P = 0.043),while quality score (AC vs. AA: P = 0.045) was identified as a source of heterogeneity for the MTHFR A1298C polymorphism and CRC risk.

Sensitivity analyses were performed to assess the stability of the included studies. When only high-quality and HWE-matched studies were included, there were differences in the results between the MTHFR C677T and A1298C polymorphisms and the risk of CRC, with the corresponding combined ORs being significantly affected as follows: Overall, four genetic models suggested that the MTHFR C677T polymorphism was a protective factor for CRC (TT vs. CC: OR=0.866, 95% CI=0.822-0.913 (FEM); TT vs. CC+CT: OR=0.879,95% CI=0.837-0.922 (FEM); CT+TT vs. CC: OR=0.966,95% CI=0.935-0.997 (FEM); T vs. C: OR=0.953, 95% CI= 0.917-0.990).In particular, when analysed by ethnic stratification, the results showed that the MTHFR C677T gene polymorphism reduced the risk of CRC in Asian, mixed-race individuals, which is consistent with previous results, but unfortunately,sensitivity analyses were not performed for Indian race due to the small number of studies on Indian race.In addition, the findings remained consistent when subgroup analyses were performed according to the source and type of control. Taken together, this suggests that the findings on MTHFR C677T and CRC susceptibility are stable. For MTHFR A1298C, when restricted to high-quality and HWE-compliant studies, the overall data suggest that the MTHFR A1298C polymorphism is a protective factor for CRC (CC vs. AA: OR = 0.909, 95% CI = 0.840-0.985 (FEM); CC vs. AA+AC: OR = 0.912, 95% CI = 0.845-0. 985 (FEM)), and race-based subgroup analyses showed additive and recessive models for mixed races (CC vs. AA: OR = 0.831, 95% CI= 0.711-0.971 (FEM); CC vs. AA+AC: OR = 0.831, 95% CI= 0.716-0.964 (FEM)), indicating that the MTHFR A1298C was able to reduce susceptibility to CRC. This is a significant difference from previous results, which were not stable enough. More details of the results of the sensitivity analyses are shown in Tables 4 and 6, and the forest plot results are shown in Figs 4 and 5.

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(Quality score >12 and consistent with HWE).

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Publication bias

In the present study, Begg funnel plot and Egger’s test were used to evaluate publication bias, and the results were shown as follows: for MTHFR C677T, the Begg funnel plot (Fig 6a) was asymmetric, and the Egger’s test: CT vs CC: PE=0.008<0.01 (the Egger’s test results for the other models are shown in Table 4), which suggested that the existence of publication bias was considered, and then the results were adjusted using the non-parametric “trimming The results were then adjusted using a non-parametric “trim and fill” approach (Fig 6b), suggesting that the current publication bias did not affect the results. For MTHFR A1298C, the funnel plot (Fig 6c) was approximately symmetrical for all models, with Egger’s test results >0.01 (Table 6), suggesting no publication bias.

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Credibility of the identified genetic associations

The study’s credibility was assessed using FPRP and BFDP. The criteria were as follows: Highly credible association: (1) statistically significant association of at least two genetic models (p-value of Z-test < 0.05); (2) I² < 50%; (3) statistical efficacy > 80%; and (4) FPRP < 0.2 and BFDP < 0.8. Less credible deterministic associations: (1) statistically significant association of at least one genetic model, p < 0.05; (2) Statistical power between 50-79%, or FPRP > 0.2 or I² > 50%. Otherwise, they were classified as “null” or “negative” associations. Table 8 displays the confidence assessment results of the association between the MTHFR C677T and A1298C polymorphisms with CRC susceptibility. In this meta-analysis, the statistical associations between the MTHFR C677T polymorphism and CRC susceptibility studies were classified as ‘false-positive results with low confidence’ after the credibility assessment. Meanwhile, the associations between the MTHFR A1298C polymorphism and CRC susceptibility studies were classified as ‘unreliable results.’

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Discussion

The development of CRC is influenced by genetic, epigenetic, dietary, and environmental factors. Research has shown that folate status, methionine levels, and alcohol consumption are all risk factors for the association between MTHFR polymorphisms and CRC [78]. Genetics is a key determinant in the development of CRC [153], and polymorphisms in cancer-related genes may influence inter-individual susceptibility to CRC [154]. Various studies have identified single nucleotide polymorphisms (SNPs) in the VEGF, CYP1B1, P53, and NOD2 genes as modifiers of CRC risk across different ethnicities. However, the association between polymorphisms in folate-related genes and susceptibility to CRC remains inconclusive. MTHFR is a key enzyme in folate metabolism that converts 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate. This conversion may play a significant role in CRC carcinogenesis. 5,10-methylenetetrahydrofolate is closely related to thymidylate synthesis, while 5-methyltetrahydrofolate promotes methionine synthesis and SAM-mediated methylation [30]. The correct operation of this metabolic pathway is crucial for maintaining normal DNA methylation, nucleotide resynthesis, and DNA repair [155]. Polymorphisms in the MTHFR gene can cause changes in enzyme activity, resulting in low levels of folate and high levels of homocysteine. This microenvironment results in DNA hypomethylation in vivo, which impacts DNA synthesis, repair, and ultimately DNA stability, as well as the expression of proto-oncogenes and oncogenes. These factors are closely linked to tumour susceptibility [156]. The role of the MTHFR gene in CRC aetiology has been extensively studied in recent years. However, no consensus has been reached, possibly due to variations in study design, geographic region, ethnicity, and dietary habits. Furthermore, there are notable variations in the incidence and mortality rates of CRC, as well as recent epidemiological trends, across different countries and regions of the world. These differences can be attributed, in part, to variations in risk factor exposure, demographic characteristics, and genetic factors (including mutations), and their impact on treatment outcomes and responses in different geographic regions and populations [157–159]. Additionally, the epidemiological characteristics of proximal and distal colon cancers differ across age and gender and are subject to multiple confounding factors. Therefore, to provide a more precise assessment of the association between the MTHFR C677T and A1298C polymorphisms with CRC susceptibility, it is necessary to conduct more detailed stratified analyses of confounding factors such as race, tumour site, and gender.

There have been 26 and 13 previous meta-analyses assessing the link between MTHFR C677T and A1298C polymorphisms and susceptibility to CRC, respectively. The most recent publications were in 2017 [15] and 2015 [41], and the studies included were mainly conducted before 2016 and 2014. The latest study included in our analysis was from 2021. It should be noted that this meta-analysis has the largest sample size to date, with included studies having maximum sample sizes of 106 and 60, compared to previous meta-analyses with maximum sample sizes of 86 and 46. When reviewing published meta-analyses, it is important to note that there can be significant variability in study results. Houlston et al. conducted a meta-analysis in 2001 to explore the relationship between MTHFR C677T and CRC susceptibility. The study found that the MTHFR C677T polymorphism was a protective factor for CRC.

However, a meta-analysis conducted by Chen et al. in 2005 found no significant correlation between the two variables. This lack of correlation may be attributed to the small sample size of included studies. In 2006, two studies [37,38] investigated the relationship between two SNP loci of MTHFR (C677T and A1298C) and CRC susceptibility for the first time. Both studies concluded that C677T was associated with CRC susceptibility. However, Yu et al. suggested that 1298CC might also have a protective effect against CRC, and Sun et al. found no statistically significant relationship between A1298C and CRC. In a study conducted by Hubner et al. in the same year, it was found that the 677TT genotype was associated with a lower risk of CRC compared to the pure CC genotype. However, it is important to note that only English articles were included in this study. Since then, 14 meta-analyses [16,20–23,25,27–31,33–35] have shown a negative relationship between MTHFR C677T and CRC susceptibility, while 5 studies [15,17,19,24,32] have concluded that there is no correlation between the two. Two articles [18,26] have shown that MTHFR C677T is a risk factor for CRC. Four studies [30,35,37,41] have found a negative relationship between MTHFR A1298C and CRC, while five studies [22,25,31,32,38] have found no statistical relationship. It is worth noting that Haerian BS et al. concluded that MTHFR A1298C is a risk factor for CRC, possibly due to genetic modelling errors.

After reviewing the meta-analyses published on the link between polymorphisms in the MTHFR gene and susceptibility to CRC, we identified several shortcomings. Firstly, only a few studies conducted sensitivity analyses on the meta-analysis results. Sensitivity analyses help to identify which studies had a significant impact on the meta-analysis results, thus providing a better understanding of the robustness and limitations of the results. Second, few studies have explored sources of heterogeneity using meta-regression equations or subgroup analyses. Finding sources of heterogeneity can help us better understand the heterogeneity of meta-analysis results and identify which factors may have had a significant impact on the meta-analysis results, which can help us better interpret the meta-analysis results and present more accurate conclusions. In addition, only 10 studies were tested for HWE, which is needed for reliable genetic association studies in meta-analyses. If the control group does not meet the HWE criteria, there may be selection bias or genotyping errors that could lead to misleading results.There was variability in the establishment of genetic models among studies, with only 10 out of 14 meta-analyses using five genetic models, which could lead to false-negative results. Additionally, Teng [26] et al. and Haerian BS [18] et al. had incorrectly established genetic models in their studies, resulting in significant variability from the results of other meta-analyses. It should be noted that previous meta-analyses did not find statistically significant associations for the probability of false positive reports. Therefore, their results may have been false positives or false negatives.

It is important to acknowledge the limitations of this meta-analysis. Firstly, it only includes published articles, which may introduce publication bias. This means that the results may not be representative of all studies and may be skewed towards those with significant results. Therefore, some research results may have been omitted. (2) This meta-analysis only includes studies published in English or Chinese, which may introduce publication bias by excluding non-significant or negative results in other languages. To address this, we used Begg’s funnel plot and Egger’s test. (3) The meta-analysis included studies of varying quality and sample size. For example, only four studies on the MTHFR C677T polymorphism and CRC risk in African populations and six studies on CRC in Indian populations were accounted for. Similarly, only four studies on the MTHFR A1298C polymorphism and CRC susceptibility in African and Indian populations, respectively, were included, along with three others. This raises the possibility that there may not be enough statistical power to explore true associations. (4) Some studies selected controls from non-cancer patients undergoing colonoscopy, while others only selected controls from asymptomatic populations. This may lead to misclassification bias as potential cancer cases may not be excluded from the control group. (5) Due to insufficient data, this meta-analysis did not adequately elucidate gene-gene and gene-environment interactions.

Despite the limitations mentioned above, the meta-analysis has several advantages over previous studies. Firstly, the sample size was significantly increased. This study represents the largest meta-analysis to date exploring the relationship between MTHFR polymorphisms and CRC susceptibility, and the data collected are much more comprehensive, providing more reliable evidence for the association between MTHFR polymorphisms and CRC risk. (2) Previous meta-analyses have assessed the association with CRC susceptibility without systematically evaluating colon and rectal cancers. Our study demonstrated that MTHFR C677T reduced susceptibility to colon cancer, but not significantly for rectal cancer. However, the MTHFR A1298C polymorphism was inversely associated with the risk of both colon and rectal cancers. This finding may be related to different oncogenic mechanisms. (3) The meta-analysis was based on unadjusted ORs and 95% CIs. To account for the effects of multiple confounding factors, such as age, sex, dietary habits (including alcohol consumption, smoking, and folate intake), tumour location, degree of differentiation, TNM stage, and other environmental factors, we conducted a more comprehensive subgroup analysis. This allowed us to explore the relationship between MTHFR polymorphisms and susceptibility to colorectal cancer. (4) Quality scores and Hardy-Weinberg equilibrium (HWE) tests were rerun for all included studies to exclude the influence of low-quality and HWE-deviating studies on the results. This improves the reliability and accuracy of the meta-analysis. (5) The sources of heterogeneity were explored using meta-regression analysis and subgroup analysis. (6) False-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) were applied to assess associations and avoid misleading false-positive results.

Conclusion

Overall, the study indicates that the MTHFR C677T gene polymorphism decreases the risk of colorectal cancer in Asian and mixed-race populations, but increases the risk in the Indian ethnic group. Furthermore, MTHFR A1298C may play a protective role in the development of CRC, although additional investigation is required to determine the specific mechanism of action and influencing factors. The findings presented here not only enhance the biological understanding of gene polymorphisms in CRC, but also offer a new perspective on the potential application of targeted induced mutations in the field of tumour diagnosis and treatment. By combining the confounding factors, an integrated scoring system can be established, which can provide a more comprehensive and accurate reference for individualized diagnosis and treatment of CRC.

Supporting Information

S1 Table. Scale for quality assessment of molecular association studies of gastric cancer.

https://doi.org/10.1371/journal.pone.0305517.s001

(DOCX)

S2 Table. plosone-checklist.

https://doi.org/10.1371/journal.pone.0305517.s002

(DOCX)

S3 Table. PRISMA 2020 checklist.

https://doi.org/10.1371/journal.pone.0305517.s003

(DOCX)

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Citation: Wang Y-w, Huang Z-y, Jin C-x, Shen X-h, He X-f, Yang C-q (2025) Unveiling the link: Evaluating MTHFR gene polymorphisms and colorectal cancer risk through meta-analysis. PLoS One 20(7): e0305517. https://doi.org/10.1371/journal.pone.0305517

About the Authors:

Yu-wei Wang

Roles: Conceptualization, Data curation, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

Affiliation: Department of Digestive internal medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

Ze-yi Huang

Roles: Conceptualization, Data curation, Methodology, Software, Validation, Visualization, Writing – review & editing

Affiliation: Changzhi Medical College, Changzhi, Shanxi Province, China

Chen-xue Jin

Roles: Data curation, Investigation, Methodology, Validation, Visualization

Affiliation: Changzhi Medical College, Changzhi, Shanxi Province, China

Xiao-hui Shen

Roles: Conceptualization, Data curation, Investigation, Software, Visualization

Affiliation: Changzhi Medical College, Changzhi, Shanxi Province, China

Xiao-feng He

Roles: Data curation, Project administration, Supervision, Writing – review & editing

E-mail: [email protected] (XH); [email protected] (CY)

Affiliation: Institute of Evidence-Based Medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi Province, China

Chang-qing Yang

Roles: Conceptualization, Data curation, Funding acquisition, Investigation, Project administration, Supervision, Writing – review & editing

E-mail: [email protected] (XH); [email protected] (CY)

Affiliation: Department of Digestive internal medicine, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China

ORICD: https://orcid.org/0000-0002-0511-2875

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