Estrogens, estrone, and estradiol are catabolized to catechol estrogens. Estrogen metabolites, such as 4-hydroxyestrone and 4-hydroxyestrone, shown to be involved in breast carcinogenesis
. Catechol-O-methyltransferase (COMT) catalyzes the O-methylation of these carcinogenic estrogens to methoxyes tradiols and methoxyestrones. In the COMT gene, a G to A transition results in an amino acid change (Val/Met) at codon 108 of soluble COMT and codon 158 of membrane-bound COMT. This amino acid change is believed to result in a 3–4-fold decrease in enzymatic activity
[6, 7]. It has been hypothesized that individuals who inherit the low activity COMT gene may be at increased risk for breast cancer because of an increased accumulation of the catechol estrogen intermediates. The potential association between the COMT Val108/158Met polymorphism and the risk of subsequent BC has evoked a huge interest from clinicians, scientists, and the public. During the past few years a large number of studies with case–control design have been carried out to investigate this topic but consistent results have not been reported. We therefore conducted a meta-analysis of the evidence obtained from all published studies in order to elucidate and provide a quantitative reassessment of the association. To our knowledge, this is the most comprehensive meta-analysis to date to evaluate the association between COMT Val108/158Met polymorphism and breast cancer risk.
We did not observe a positive relationship between COMT Val108/158Met polymorphism and breast cancer risk either overall or among subgroups of women defined by ethnicity, menopausal status or sources of the control population. In previous studies, overall the findings were inconsistent. Lavigne et al. observed a large increase in the risk of breast cancer among postmenopausal obese women carrying the COMT-LL genotype, and an inverse association among premenopausal women with the relative risk (RR) for COMT-LL stronger among postmenopausal women with high BMI
. Thompson et al. reported positive associations for the COMT-HL and COMT-LL genotypes among premenopausal women and found that modification of RRs by BMI was highest among premenopausal women with a high BMI
. A comprehensive study of the entire estrogen-metabolizing pathway (CYP17, CYP1A1, COMT) also reported that breast cancer is only associated with the low activity COMT genotype in women with a high BMI and that the COMT-LL genotype was strongly associated with breast cancer risk, with an adjusted OR of as high as 4.02
. In contrast to the other studies but in line with the findings of the current study, Lajin et al. did not observe any association between one or two copies of the COMT-L allele and breast cancer risk, and did not find strong modification of RR estimates by menopausal status
. In an effort to shed some light on the impact of COMT Val108/158Met polymorphism on breast cancer risk, two previous meta-analyses
[17, 18] were conducted almost at the same time to explore the relationship between COMT Val108/158Met polymorphism and breast cancer. Ding et al.
 examined the effect of COMT Val158Met polymorphism on breast cancer risk by combining results in meta-analysis. They concluded that COMT Val158Met polymorphism was significantly associated with increased breast cancer risk in European population. However, Mao et al.
 did not find any relationship between COMT Val158Met polymorphism and breast cancer risk in any genetic models including among Caucasian, Asian, premenopausal, and postmenopausal women in their meta-analysis, which was consistent with the findings of our study. The discrepancy in previously reported findings was most probably because that the previous studies with relatively small sample size may have insufficient statistical power to detect the exact effect or may have generated a fluctuated risk estimate. However, in our study, large number of cases and controls were pooled from all published studies, which greatly increased statistical power of the analysis and provided enough evidence for us to draw a safe and reliable conclusion.
Heterogeneity is a potential problem that may affect the interpretation of the results. The present meta-analysis showed that there was large heterogeneity between studies (table
2). Common reasons for heterogeneity may include differences in the studied populations (e.g., ethnicity, menopausal status), or in methods (e.g., genotyping), or in sample selection (e.g., source of control populations), or it may be due to interaction with other risk factors (e.g., BRCA variants). Finding of the source of heterogeneity is one of the most important goals of a meta-analysis. Therefore, we stratified the studies according to ethnicity, source of control subjects of the studies, and menopausal status. Subsequent subgroup analysis stratified by ethnicity, source of control subjects, and menopausal status identified large heterogeneity as well, indicating that menopausal status, ethnicity or source of control subjects contributed little to the existence of overall heterogeneity. Unfortunately, our study had insufficient information for subgroup analysis to detect whether the variants in BRCA gene might be great sources of heterogeneity. We found that in three studies
[33, 41, 70] the genotypic frequencies showed significant deviation from the expected frequencies based on Hardy–Weinberg equilibrium and two studies
[66, 73] provide insufficient data for calculating P value of HWE in the control populations. Excluding these five studies did not alter the heterogeneity between studies. However, when heterogeneity between the studies exists, the results could be interpreted in the context of cumulative meta-analysis, which provides a measure of how much the genetic effect changes as more data accumulate over time
. In our study, the results of cumulative meta-analysis for dominant model LL+HL versus HH showed stability in pooled odds ratio after the year 2007 in the overall populations, which provide evidence for drawing safe conclusion about the insignificant association between COMT Val158Met polymorphism and breast cancer risk.
Some limitations of this meta-analysis should be acknowledged. First, some studies found significant associations between COMT Val108/158Met polymorphism and breast cancer risk in several subgroups of populations, such as associations among postmenopausal women with a low body mass index (BMI)
[10, 11], a high BMI
 or women at young ages
. It is difficult for a meta-anlysis to derive such specific associations because the results from previous studies were not presented in a uniform standard. Second, our results were based on unadjusted estimates and a more precise analysis should be carried out if individual data were available, this would allow for adjustment by other covariates including age, BMI, ethnicity, lifestyle, and environmental factors. Third, all of the studies were performed in Asian and Caucasian populations. Further studies are needed in other ethnic populations because of possible ethnic differences of the COMT polymorphisms. In spite of these, our present meta-analysis also had some advantages. First, substantial number of cases and controls were pooled from all publications concerned with COMT Val158Met polymorphism and BC risk, which greatly increased statistical power of the analysis and provided enough evidence for us to draw a safe conclusion. Second, the quality of case–control studies included in this meta-analysis was satisfactory according to our selection criteria. Third, no publication bias was detected in this meta-analysis, which indicated that the pooled results of our study should be reliable.
In conclusion, this meta-analysis suggests that the COMT Val158Met polymorphism may not be associated with breast cancer risk. However, it is necessary to conduct large sample studies using standardized unbiased genotyping methods, homogeneous breast cancer patients, and well-matched controls. Moreover, gene-gene and gene-environment interactions should also be considered in the analysis. Such studies taking these factors into account may eventually lead to a better, more comprehensive understanding of the association between COMT Val158Met polymorphism and BC risk.