Abstract
Background
Epidemiological studies consistently indicate that alcohol consumption is an independent risk factor for female breast cancer (BC). Although the aldehyde dehydrogenase 2 (ALDH2) polymorphism (rs671: Glu>Lys) has a strong effect on acetaldehyde metabolism, the association of rs671 with BC risk and its interaction with alcohol intake have not been fully elucidated. We conducted a pooled analysis of 14 case‐control studies, with individual data on Asian ancestry women participating in the Breast Cancer Association Consortium.
Methods
We included 12,595 invasive BC cases and 12,884 controls for the analysis of rs671 and BC risk, and 2,849 invasive BC cases and 3,680 controls for the analysis of the gene‐environment interaction between rs671 and alcohol intake for BC risk. The pooled odds ratios (OR) with 95% confidence intervals (CI) associated with rs671 and its interaction with alcohol intake for BC risk were estimated using logistic regression models.
Results
The Lys/Lys genotype of rs671 was associated with increased BC risk (OR = 1.16, 95% CI 1.03–1.30, p = 0.014). According to tumor characteristics, the Lys/Lys genotype was associated with estrogen receptor (ER)‐positive BC (OR = 1.19, 95% CI 1.05–1.36, p = 0.008), progesterone receptor (PR)‐positive BC (OR = 1.19, 95% CI 1.03–1.36, p = 0.015), and human epidermal growth factor receptor 2 (HER2)‐negative BC (OR = 1.25, 95% CI 1.05–1.48, p = 0.012). No evidence of a gene‐environment interaction was observed between rs671 and alcohol intake (p = 0.537).
Conclusion
This study suggests that the Lys/Lys genotype confers susceptibility to BC risk among women of Asian ancestry, particularly for ER‐positive, PR‐positive, and HER2‐negative tumor types.
Keywords: acetaldehyde, alcohol drinking, aldehyde dehydrogenase‐2, breast cancer, single nucleotide polymorphism
1. INTRODUCTION
Epidemiological studies consistently indicate that alcohol is an independent risk factor for female breast cancer (BC) (Singletary & Gapstur, 2001). The International Agency for Research on Cancer concluded that there is sufficient evidence to classify alcohol as a carcinogen for female BC (IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, 2010). One hypothesized mechanism behind alcohol‐related breast carcinogenesis is the involvement of acetaldehyde, a metabolite of ethanol. An impact of acetaldehyde on carcinogenesis for several types of alcohol‐induced cancers has been shown in experimental models (Brooks & Theruvathu, 2005). Molecular epidemiological studies demonstrated a gene‐environment interaction between a functional aldehyde dehydrogenase 2 (ALDH2) polymorphism (rs671: Glu>Lys, OMIM: 100650) and alcohol intake for esophageal and upper digestive tract cancers in East Asian countries (Matsuo et al., 2001; Oze et al., 2010), where rs671 is prevalent (Li et al., 2009). These studies support the hypothesis that acetaldehyde is a carcinogen. The Glu/Lys heterozygotes of rs671 have far less than half of ALDH2 activity of Glu/Glu homozygotes, and the Lys/Lys homozygotes have no detectable ALDH2 activity, which leads to high acetaldehyde concentrations upon alcohol intake in individuals harboring the Lys allele (Crabb, Edenberg, Bosron, & Li, 1989). Therefore, exploring the association of rs671 with BC risk and its interaction with alcohol intake is one approach to elucidate whether acetaldehyde is a causative agent for breast carcinogenesis. To date, evidence of an association of rs671 with BC risk is scarce; statistically significant associations have not been observed in case‐control studies in Japan (456 cases and 912 controls) (Kawase et al., 2009) Korea (346 cases and 377 controls) (Choi et al., 2003) or Thailand (561 cases and 486 controls) (Sangrajrang et al., 2010). We conducted a pooled analysis of individual genetic and alcohol consumption data for women of Asian ancestry participating in studies in the Breast Cancer Association Consortium (BCAC) with at least 18 times larger sample size than previous studies.
2. METHODS
2.1. Study population
We used data from 14 case‐control studies in the BCAC. Table 1 shows participating studies contributing to this pooled analysis. All study participants were of Asian ancestry and recruited from studies conducted in Asian countries, Canada, and the USA. Eight studies were hospital‐based, five were population‐based, and one included hospital‐based cases and population‐based controls. We included 12,595 BC cases and 12,884 controls for the analysis of rs671 and BC risk. For the analysis of the gene‐environment interaction between rs671 and alcohol intake for BC risk, we included 2,849 BC cases and 3,680 controls after excluding participants with missing values for alcohol intake from seven studies. All studies were approved by their local ethics review boards, and all participants provided informed consent. This investigation was approved by a human research investigations committee at Aichi Cancer Center.
Table 1.
List of participating studies and number of participants
| Study acronym | Study name | Study design | Country | Subjects of analysis for rs671 | Subjects of analysis for GE interaction | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Case | Control | Lys allele frequency among cases (%) | Lys allele frequency among controls (%) | Case | Control | Lys allele frequency among cases (%) | Lys allele frequency among controls (%) | ||||
| ACP | Asia Cancer Program | Hospital based case‐control study | Thailand | 830 | 1,060 | 8.9 | 8.0 | — | — | — | — |
| CBCS | Canadian Breast Cancer Study | Population‐based case‐control study | Canada | 252 | 170 | 28.6 | 20.0 | — | — | — | — |
| HERPACC | Hospital‐based Epidemiologic Research Program at Aichi Cancer | Hospital‐based case‐control study | Japan | 792 | 1,659 | 29.9 | 28.3 | 783 | 1,632 | 30.1 | 28.6 |
| HKBCS | Hong Kong Breast Cancer Study | Hospital‐based case‐control study | China | 466 | 451 | 32.1 | 28.4 | — | — | — | — |
| KOHBRA | Korean Hereditary Breast Cancer Study | Population‐based case‐control study | Korea | 1,251 | 665 | 17.1 | 15.9 | 413 | 601 | 6.8 | 15.4 |
| LAABC | Los Angeles County Asian‐American Breast Cancer Case‐Control Study | Population‐based case‐control study | USA | 808 | 990 | 24.9 | 27.5 | 808 | 990 | 24.9 | 27.5 |
| MYBRCA | Malaysian Breast Cancer Genetic Study | Hospital‐based case‐control study | Malaysia | 1,408 | 1,866 | 24.5 | 22.6 | — | — | — | — |
| NC‐BCFR | Northern California Breast Cancer Family Registry | Population‐based case‐control study | USA | 446 | 52 | 21.4 | 21.2 | 400 | 46 | 22.4 | 23.9 |
| NGOBCS | Nagano Breast Cancer Study | Hospital‐based case‐control study | Japan | 366 | 366 | 25.4 | 23.6 | 366 | 365 | 25.4 | 23.7 |
| SBCGS | Shanghai Breast Cancer Genetic Study | Population‐based case‐control study, cohort study | China | 1,644 | 1,827 | 24.9 | 23.9 | 5 | 46 | 10.0 | 7.6 |
| SEBCS | Seoul Breast Cancer Study | Hospital‐based case‐control study | Korea | 2,129 | 2,236 | 16.9 | 15.1 | 74 | — | 2.7 | — |
| SGBCC | Singapore Breast Cancer Cohort | Hospital based breast cancer cohort and population‐based controls | Singapore | 775 | 798 | 20.8 | 23.6 | — | — | — | — |
| TBCS | IARC‐Thai Breast Cancer Study | Hospital‐based case‐control study | Thailand | 138 | 253 | 6.9 | 11.7 | — | — | — | — |
| TWBCS | Taiwanese Breast Cancer Study | Hospital‐based case‐control study | Taiwan | 1,290 | 491 | 27.8 | 31.5 | — | — | — | — |
| Total | 12,595 | 12,884 | 22.1 | 21.4 | 2,849 | 3,680 | 22.8 | 25.3 | |||
Abbreviation: GE interaction, gene‐environment interaction.
2.2. Genotyping methods
Genotyping was carried out using the iCOGS array (http://ccge.medschl.cam.ac.uk/research/consortia/icogs/), or the OncoArray (https://support.illumina.com/downloads/infinium-oncoarray-500k-v1-0-product-files.html). Details of array design, genotyping, postgenotyping quality control, and imputation have been provided elsewhere (Michailidou et al., 2013, 2017). The rs671 SNP on ALDH2 was a candidate SNP selected on the basis of specific hypotheses described above.
To adjust for potential population stratification, principal components analyses (PCA) were carried out separately for Asian subgroups. Briefly, PCA was performed based on a subset of 37,000 uncorrelated SNPs for the iCOGS data and based on 33,661 uncorrelated SNPs for the OncoArray data. For the present analyses, we used two Asian principal components for the iCOGS dataset and 10 Asian principal components for the OncoArray dataset as covariates. Further details have been provided in previous articles (Michailidou et al., 2013, 2017).
2.3. Alcohol assessment
Each study ascertained alcohol intake via self‐reported questionnaire. Daily alcohol intake in grams was determined by summing the product of frequency of consumption of specified alcoholic beverages (beer, wine, and other alcoholic beverages) by the alcohol content of each beverage using national estimates of alcohol content for that country. The exposure period was the year preceding recruitment. A multistep harmonization procedure was used to reconcile differences in individual study questionnaires.
2.4. Statistical analysis
To assess the associations of rs671 with BC risk, we estimated odds ratios (ORs) with 95% confidence intervals (CIs) by unconditional logistic regression models using the Glu/Glu genotype as reference. This was done separately for iCOGS and OncoArray datasets, and results were combined by a fixed‐effects meta‐analysis. The ORs were adjusted for age, Asian principal components, and study. We also evaluated the associations by tumor characteristics (estrogen receptor, ER; progesterone receptor, PR; human epidermal growth factor receptor 2, HER2) and tumor subtypes (luminal [either ER or PR positive, HER2 negative], triple positive [ER, PR, HER2 positive], HER2 enrich [ER, PR negative, HER2 positive], triple negative [ER, PR, HER2 negative]) using cases with these specific characteristics. Heterogeneity by tumor characteristics and between studies was assessed using Cochran's Q test. We assessed the gene‐environment interaction between rs671 and alcohol intake by including an interaction term. Alcohol intake was classified in three ways: 1) two categories (none, any alcohol intake); 2) three categories (none, <15 g ethanol/day, ≥15 g ethanol/day); and 3) four categories (none, <15 g ethanol/day, 15–30 g ethanol/day, ≥30 g ethanol/day). We also performed stratified analyses by menopausal status: women with missing menopausal status were considered premenopausal if they were ≤50 years or postmenopausal if >50 years. All statistical analyses were performed using Stata version 15.1 (Stata Corp., College Station, TX, USA), with a P value <0.05 considered to be statistically significant.
3. RESULTS
Demographic characteristics of participants are shown in Table 2. The median age was 50 years for both cases and controls, with a higher proportion of women in the oldest age groups for cases. The proportion of nondrinkers and heavy drinkers (≥15 g ethanol/day) was higher among controls than cases, possibly due to the smaller number of unknown category in controls (71.4%) than in cases (77.4%). The distributions of tumor characteristics among cases were 7,648 ER positive (60.7%), 6,308 PR positive (50.1%), and 3,054 HER2 positive (24.3%) for participants included in the analysis of rs671 alone and, 1,871 ER positive (65.7%), 1,620 PR positive (56.9%), and 552 HER2 positive (19.4%) for those in the analysis of gene‐environment interaction, respectively.
Table 2.
Characteristics of cases and controls
| Subjects of analysis for rs671 | Subjects of analysis for GE interaction | |||||||
|---|---|---|---|---|---|---|---|---|
| Cases (N = 12,595) | (%) | Control (N = 12,884) | (%) | Cases (N = 2,849) | (%) | Control (N = 3,680) | (%) | |
| Age (years) | ||||||||
| Median (range) | 50 (20–91) | 50 (15–92) | 50 (20–81) | 50 (19–86) | ||||
| ≦29 | 205 | 1.6 | 300 | 2.3 | 60 | 2.1 | 68 | 1.9 |
| 30–39 | 1,641 | 13.0 | 1,254 | 9.7 | 421 | 14.8 | 408 | 11.1 |
| 40–49 | 4,255 | 33.8 | 4,547 | 35.3 | 845 | 29.7 | 1,234 | 33.5 |
| 50–59 | 3,847 | 30.5 | 4,179 | 32.4 | 830 | 29.1 | 1,117 | 30.4 |
| 60–69 | 1,911 | 15.2 | 2,138 | 16.6 | 498 | 17.5 | 638 | 17.3 |
| ≧70 | 736 | 5.8 | 466 | 3.6 | 195 | 6.8 | 215 | 5.8 |
| Alcohol consumption† | ||||||||
| g/day (mean ± SD) | 31.2 ± 91.2 | 30.5 ± 83.0 | 31.2 ± 91.2 | 30.5 ± 83.0 | ||||
| Nondrinker | 1,746 | 13.9 | 2,348 | 18.2 | 1,746 | 61.3 | 2,348 | 63.8 |
| <15 g ethanol/day | 895 | 7.1 | 1,052 | 8.2 | 895 | 31.4 | 1,052 | 28.6 |
| ≥15 g ethanol/day | 208 | 1.7 | 280 | 2.2 | 208 | 7.3 | 280 | 7.6 |
| Unknown | 9,746 | 77.4 | 9,204 | 71.4 | ||||
| ALDH2 Glu/Glu genotype | ||||||||
| g/day (mean ± SD) | 42.4 ± 103.9 | 44.8 ± 102.0 | 42.4 ± 103.9 | 44.8 ± 102.0 | ||||
| Nondrinker | 828 | 10.6 | 1,040 | 12.9 | 828 | 48.0 | 1,040 | 50.7 |
| <15 g ethanol/day | 719 | 9.2 | 774 | 9.6 | 719 | 41.7 | 774 | 37.8 |
| ≥15 g ethanol/day | 178 | 2.3 | 236 | 2.9 | 178 | 10. | 236 | 11.5 |
| Unknown | 6,056 | 77.8 | 5,988 | 74.5 | ||||
| ALDH2 Glu/Lys genotype | ||||||||
| g/day (mean ± SD) | 16.1 ± 68.5 | 13.3 ± 43.0 | 16.1 ± 68.5 | 13.3 ± 43.0 | ||||
| Nondrinker | 745 | 18.3 | 1,076 | 25.8 | 745 | 78.6 | 1,076 | 77.1 |
| <15 g ethanol/day | 173 | 4.3 | 276 | 6.6 | 173 | 18.3 | 276 | 19.8 |
| ≥15 g ethanol/day | 30 | 0.7 | 44 | 1.1 | 30 | 3.2 | 44 | 3.2 |
| Unknown | 3,122 | 76.7 | 2,779 | 66.6 | ||||
| ALDH2 Lys/Lys genotype | ||||||||
| g/day (mean ± SD) | 0.4 ± 3.4 | 0.5 ± 5.1 | 0.4 ± 3.4 | 0.5 ± 5.1 | ||||
| Nondrinker | 232 | 99.2 | 173 | 98.3 | 232 | 99.2 | 173 | 98.3 |
| <15 g ethanol/day | 2 | 0.8 | 3 | 1.7 | 2 | 0.8 | 3 | 1.7 |
| ≥15 g ethanol/day | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Unknown | 0 | 0 | 0 | 0 | ||||
| Menopausal status | ||||||||
| Premenopausal | 3,690 | 29.3 | 5,234 | 40.6 | 836 | 29.3 | 1,393 | 37.9 |
| Postmenopausal | 4,287 | 34.0 | 4,830 | 37.5 | 879 | 30.9 | 1,246 | 33.9 |
| Unknown | 4,618 | 36.7 | 2,820 | 21.9 | 1,134 | 39.8 | 1,041 | 28.3 |
| ER status | ||||||||
| Positive | 7,648 | 60.7 | 1,871 | 65.7 | ||||
| Negative | 3,701 | 29.4 | 658 | 23.1 | ||||
| Unknown | 1,246 | 9.9 | 320 | 11.2 | ||||
| PR status | ||||||||
| Positive | 6,308 | 50.1 | 1,620 | 56.9 | ||||
| Negative | 3,776 | 30.0 | 865 | 30.4 | ||||
| Unknown | 2,511 | 19.9 | 364 | 12.8 | ||||
| HER2 status | ||||||||
| Positive | 3,054 | 24.3 | 552 | 19.4 | ||||
| Negative | 4,054 | 32.2 | 557 | 19.6 | ||||
| Unknown | 5,487 | 43.6 | 1,740 | 61.1 | ||||
Abbreviations: ALDH2, aldehyde dehydrogenase 2; ER, estrogen receptor; GE interaction, gene‐environment interaction; HER2, human epidermal growth factor receptor 2; PR, progesterone receptor.
Exposure period was the year preceding recruitment.
Table 3 presents the associations of rs671 with BC risk. Overall, the Lys/Lys genotype was associated with increased BC risk, with OR of 1.16 (95% CI = 1.03–1.30, p = 0.014) relative to Glu/Glu genotype. According to tumor characteristics, we observed an association of the Lys/Lys genotype with ER‐positive BC (OR = 1.19, 95% CI 1.05–1.36, p = 0.008), PR‐positive BC (OR = 1.19, 95% CI 1.03–1.36, p = 0.015), and HER2‐negative BC (OR = 1.25, 95% CI 1.05–1.48, p = 0.012), but not with ER‐negative BC (OR = 1.07, 95% CI 0.90–1.27, p = 0.453), PR‐negative BC (OR = 1.13, 95% CI 0.95–1.34, p = 0.176), or HER2‐positive BC (OR = 1.19, 95% CI 0.97–1.48, p = 0.102), although no statistically significant heterogeneity was observed by tumor characteristics. According to tumor subtypes, the Lys/Lys genotype was only associated with luminal BC (OR = 1.30, 95% CI 1.09–1.55, p = 0.004), and not with other subtypes (Table 4). No evidence of heterogeneity was also observed by menopausal status (Table S1).
Table 3.
Association between ALDH2 genotype and breast cancer risk
| ALDH2 genotype | p for heterogeneity between tumor characteristics | ||||
|---|---|---|---|---|---|
| Glu/Glu | Glu/Lys | Lys/Lys | For Glu/Lys | For Lys/Lys | |
| Overall | |||||
| Cases/controls | 7,781/8,038 | 4,070/4,175 | 744/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.03 (0.97–1.08, p = 0.350) | 1.16 (1.03–1.30, p = 0.014) | ||
| ER status | |||||
| Positive | |||||
| Cases/controls | 4,636/8,038 | 2,531/4,175 | 481/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.01 (0.95–1.08, p = 0.669) | 1.19 (1.05–1.36, p = 0.008) | 0.447 | 0.329 |
| Negative | |||||
| Cases/control | 2,321/8,038 | 1,187/4,175 | 193/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.05 (0.97–1.14, p = 0.257) | 1.07 (0.90–1.27, p = 0.453) | ||
| PR status | |||||
| Positive | |||||
| Cases/controls | 3,842/8,038 | 2,066/4,175 | 400/671 | ||
| OR (95% CI)† | 1 (ref.) | 0.98 (0.92–1.05, p = 0.591) | 1.19 (1.03–1.36, p = 0.015) | 0.410 | 0.653 |
| Negative | |||||
| Cases/control | 2,333/8,038 | 1,238/4,175 | 205/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.02 (0.95–1.11, p = 0.545) | 1.13 (0.95–1.34, p = 0.176) | ||
| HER2 status | |||||
| Positive | |||||
| Cases/control | 1,961/8,038 | 940/4,175 | 153/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.02 (0.92–1.14, p = 0.674) | 1.19 (0.97–1.48, p = 0.102) | 1.000 | 0.720 |
| Negative | |||||
| Cases/control | 2,521/7,841 | 1,287/4,175 | 246/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.02 (0.93–1.11, p = 0.722) | 1.25 (1.05–1.48, p = 0.012) | ||
Abbreviations: ALDH2, aldehyde dehydrogenase 2; CI, confidence intervals; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; OR, odds ratios; PR, progesterone receptor.
ORs were adjusted for age (continuous), Asian principal components and study site.
Table 4.
Association between ALDH2 genotype and breast cancer risk by tumor subtypes
| ALDH2 genotype | p for heterogeneity between tumor characteristics | ||||
|---|---|---|---|---|---|
| Glu/Glu | Glu/Lys | Lys/Lys | For Glu/Lys | For Lys/Lys | |
| Luminal | |||||
| Cases/controls | 1,950/8,038 | 979/4,175 | 198/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.00 (0.92–1.10, p = 0.916) | 1.30 (1.09–1.55, p = 0.004) | 0.452 | 0.755 |
| Triple positive | |||||
| Cases/controls | 1,202/8,038 | 583/4,175 | 93/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.03 (0.91–1.16, p = 0.640) | 1.19 (0.93–1.53, p = 0.164) | ||
| HER2 enrich | |||||
| Cases/controls | 694/8,038 | 322/4,175 | 55/671 | ||
| OR (95% CI)† | 1 (ref.) | 0.96 (0.83–1.11, p = 0.557) | 1.12 (0.83–1.51, p = 0.453) | ||
| Triple negative | |||||
| Cases/control | 546/8,038 | 310/4,175 | 46/671 | ||
| OR (95% CI)† | 1 (ref.) | 1.13 (0.97–1.32, p = 0.108) | 1.11 (0.81–1.53, p = 0.519) | ||
Abbreviations: ALDH2, aldehyde dehydrogenase 2; CI, confidence intervals; HER2, human epidermal growth factor receptor 2; OR, odds ratios.
ORs were adjusted for age (continuous), Asian principal components and study site.
Figure S1 and Figure S2 show the forest plots of study‐specific ORs for the association between rs671 and BC risk. With regard to the association between the Glu/Lys genotype and BC risk, there was no evidence of between‐study heterogeneity (p for heterogeneity = 0.380). In contrast, significant between‐study heterogeneity was observed for the association of the Lys/Lys genotype with BC risk (p for heterogeneity = 0.003), which was mainly attributable to a strong positive association for CBCS and a strong inverse association for ACP and TWBCS. However, exclusion of these studies did not alter the significant association of the Lys/Lys genotype with BC risk (OR = 1.18, 95% CI 1.05–1.33, p = 0.008) and there was no longer evidence of between‐study heterogeneity (p for heterogeneity = 0.133). Furthermore, when we repeated analyses using random effects meta‐analyses to calculate summary study‐specific estimates, the results did not change substantially (Table S2).
Stratified analyses by alcohol intake categories assessing a gene‐environment interaction between rs671 and alcohol intake showed no evidence of interaction, although the sample size is small compared to the analysis of rs671 and BC risk (Table S3, p for interaction = 0.537).
4. DISCUSSION
In this study, we found that the Lys/Lys genotype of rs671 was associated with increased BC risk among women of Asian ancestry. No evidence of interaction was observed between rs671 and alcohol intake. This is the largest study to date to perform this evaluation quantitatively using high‐quality individual‐level data for Asian women.
Several epidemiological studies have reported a gene‐environment interaction between rs671 and alcohol intake for several types of cancer (Hiraki et al., 2007; Ishioka et al., 2018; Masaoka et al., 2016; Matsuo et al., 2001, 2013; Oze et al., 2010). Our findings are not consistent with our hypothesis of gene‐environment interaction between rs671 and alcohol intake. Considering the established impact of rs671 on cancer risk, this lack of interaction suggests that acetaldehyde may be less influential in breast carcinogenesis. Other biological mechanisms for alcohol‐related breast carcinogenesis have been hypothesized, including increased circulating estrogens and androgens, enhancement of mammary gland susceptibility to carcinogenesis, increased mammary carcinogen DNA damage, interference of folate metabolism by alcohol, and greater potential for invasiveness into BC cells (Bernstein & Ross, 1993; Singletary & Gapstur, 2001; Singletary & McNary, 1994; Stolzenberg‐Solomon et al., 2006). To better understand the etiologic nature of the effect of alcohol on breast carcinogenesis, further investigations are needed.
We observed an association of the Lys/Lys genotype with increased BC risk. Because individuals with the Lys/Lys genotype have no detectable ALDH2 activity and almost completely refrain from drinking due to severe adverse reactions caused by acetaldehyde (e.g., facial flushing, nausea and headache) (Matsuo et al., 2006), the observed genetic association suggests that the Lys/Lys genotype confers susceptibility to BC risk independently of alcohol intake. ALDH2 plays a key role in removal of not only ethanol‐derived acetaldehyde, but also other toxic endogenous aldehydes such as 4‐hydroxy‐2‐nonenal (4‐HNE) and malondialdehyde (Chen, Ferreira, Gross, & Mochly‐Rosen, 2014). These endogenous aldehydes have been reported to cause DNA damage and might be related to breast carcinogenesis (Chen et al., 2014; Garaycoechea et al., 2018). In addition, we did not find an association of the Glu/Lys genotype with BC risk. This suggest that ALDH2 activity of the Glu/Lys homozygotes may be sufficient for detoxifying toxic endogenous aldehydes related to breast carcinogenesis. In contrast, the Lys/Lys homozygotes have no detectable ALDH2 activity, thus may not tolerate these endogenous aldehydes. Furthermore, the Lys/Lys genotype was associated with increased risk only in hormone receptor positive BC, and not in hormone receptor negative BC. These results suggest that the biological mechanism could be through a hormonal receptor mediated pathway (Zhang, Man, Zhao, Dong, & Ma, 2014). The evidence of an association of rs671 with BC risk is scarce and may warrant additional evaluation in future studies.
The strengths of this investigation include the analysis of individual‐level data from a large sample of Asian women, allowing us to obtain stable, and precise summary estimates of the association of rs671 with BC risk. Other strengths are the uniform genotyping procedures and quality‐control measures undertaken for the iCOGS and the OncoArray, respectively. We were also able to control for population stratification by including Asian principal components as a covariate to control for residual genetic heterogeneity. Furthermore, the Lys allele of rs671 is only prevalent in East Asia, and has not been found in Caucasians or Africans (Li et al., 2009). Thus, this analysis is unique and can be performed only among Asian women. Several limitations also warrant consideration. First, we could not evaluate the association between alcohol intake and BC risk because there were a lot of missing data on potential confounding factors (e.g., smoking, estrogen‐related factors) and we were not able to control for them. However, genotypes are fixed at birth and these factors cannot influence genotypes; therefore, our results about rs671 and BC risk may be unbiased even though we did not adjust for these factors. Second, even though all study participants were of Asian ancestry, the heterogeneity across study populations, designs, and methods are potential limitations. Third, careful interpretation of results from the analysis of gene‐environment interaction and stratified analyses is necessary because we had a limited number of participants in some sub‐groups and did not adjust for multiple comparisons.
In conclusion, we observed an association between the Lys/Lys genotype of rs671 and increased BC risk. Among women of Asian ancestry, this study suggests that the Lys/Lys genotype confers susceptibility to BC risk, particularly for ER‐positive, PR‐positive, and HER2‐negative tumor types. These findings warrant further investigation in future studies.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
Supporting information
ACKNOWLEDGMENTS
We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians, and administrative staff who have enabled this work to be carried out. The COGS study would not have been possible without the contributions of the following: Per Hall (COGS); Douglas F. Easton, Paul Pharoah, Kyriaki Michailidou, Manjeet K. Bolla, Qin Wang (BCAC), Joe Dennis, Alison M. Dunning, Andrew Lee, and Ed Dicks, Craig Luccarini and the staff of the Centre for Genetic Epidemiology Laboratory, Javier Benitez, Anna Gonzalez‐Neira and the staff of the CNIO genotyping unit, Jacques Simard and Daniel C. Tessier, Francois Bacot, Daniel Vincent, Sylvie LaBoissière and Frederic Robidoux and the staff of the McGill University and Génome Québec Innovation Centre, Stig E. Bojesen, Sune F. Nielsen, Borge G. Nordestgaard, and the staff of the Copenhagen DNA laboratory, and Julie M. Cunningham, Sharon A. Windebank, Christopher A. Hilker, Jeffrey Meyer and the staff of Mayo Clinic Genotyping Core Facility. The ACP study wishes to thank the participants in the Thai Breast Cancer study. Special Thanks also go to the Thai Ministry of Public Health (MOPH), doctors and nurses who helped with the data collection process. Finally, the study would like to thank Dr. Prat Boonyawongviroj, the former Permanent Secretary of MOPH and Dr. Pornthep Siriwanarungsan, the former Department Director‐General of Disease Control who has supported the study throughout. CBCS thanks study participants, co‐investigators, collaborators, and staff of the Canadian Breast Cancer Study, and project coordinators Agnes Lai and Celine Morissette. HKBCS thanks Hong Kong Sanatorium and Hospital, Dr. Ellen Li Charitable Foundation, The Kerry Group Kuok Foundation, National Institute of Health 1R03CA130065, and the North California Cancer Center for support. We thank all investigators of the KOHBRA (Korean Hereditary Breast Cancer) Study. LAABC thanks all the study participants and the entire data collection team, especially Annie Fung and June Yashiki. MYBRCA thanks study participants and research staff (particularly Patsy Ng, Nurhidayu Hassan, Yoon Sook‐Yee, Daphne Lee, Lee Sheau Yee, Phuah Sze Yee and Norhashimah Hassan) for their contributions and commitment to this study. SGBCC thanks the participants and research coordinator Ms Tan Siew Li.
Ugai T, Milne RL, Ito H, et al. The functional ALDH2 polymorphism is associated with breast cancer risk: A pooled analysis from the Breast Cancer Association Consortium. Mol Genet Genomic Med. 2019;7:e707 10.1002/mgg3.707
Funding information
BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union's Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B‐CAST respectively), and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH‐F2‐2009‐223175) (COGS). The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Genotyping of the OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/A16563 and the PERSPECTIVE project supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH‐129344) and, the Ministère de l’Économie, Science et Innovation du Québec through Genome Québec and the PSRSIIRI‐701 grant, and the Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH‐F2‐2009–223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post‐Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME‐ON initiative), the Department of Defence (W81XWH‐10‐1‐0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, and Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The ACP study is funded by the Breast Cancer Research Trust, UK. CBCS is funded by the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health Research. The HERPACC was supported by MEXT Kakenhi (No. 170150181 and 26253041) from the Ministry of Education, Science, Sports, Culture, and Technology of Japan, by a Grant‐in‐Aid for the Third Term Comprehensive 10‐Year Strategy for Cancer Control from Ministry Health, Labour, and Welfare of Japan, by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour, and Welfare of Japan, by National Cancer Center Research and Development Fund, and "Practical Research for Innovative Cancer Control (15ck0106177h0001)" from Japan Agency for Medical Research and development, AMED, and Cancer Bio Bank Aichi. The KOHBRA study was partially supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). LAABC is supported by grants (1RB‐0287, 3PB‐0102, 5PB‐0018, 10PB‐0098) from the California Breast Cancer Research Program. MYBRCA is funded by research grants from the Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Malaysia. MYMAMMO is supported by research grants from Yayasan Sime Darby LPGA Tournament and Malaysian Ministry of Higher Education (RP046B‐15HTM). The Northern California Breast Cancer Family Registry (NC‐BCFR) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The NGOBCS was supported by National Cancer Center Research and Development Fund. The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, UMCA182910, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The scientific development and funding of this project were, in part, supported by the Genetic Associations and Mechanisms in Oncology (GAME‐ON) Network U19 CA148065. SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012‐0000347). SGBCC is funded by the NUS start‐up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore Consortium of Cohort Studies‐Multi‐ethnic cohort (SCCS‐MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. The TBCS was funded by The National Cancer Institute Thailand. The TWBCS is supported by the Institute of Biomedical Sciences, Academia Sinica, Taiwan.
REFERENCES
- Bernstein, L. , & Ross, R. K. (1993). Endogenous hormones and breast cancer risk. Epidemiologic Reviews, 15(1), 48–65. 10.1093/oxfordjournals.epirev.a036116 [DOI] [PubMed] [Google Scholar]
- Brooks, P. J. , & Theruvathu, J. A. (2005). DNA adducts from acetaldehyde: Implications for alcohol‐related carcinogenesis. Alcohol, 35(3), 187–193. 10.1016/j.alcohol.2005.03.009 [DOI] [PubMed] [Google Scholar]
- Chen, C. H. , Ferreira, J. C. , Gross, E. R. , & Mochly‐Rosen, D. (2014). Targeting aldehyde dehydrogenase 2: New therapeutic opportunities. Physiological Reviews, 94(1), 1–34. 10.1152/physrev.00017.2013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Choi, J.‐Y. , Abel, J. , Neuhaus, T. , Ko, Y. , Harth, V. , Hamajima, N. , … Kang, D. (2003). Role of alcohol and genetic polymorphisms of CYP2E1 and ALDH2 in breast cancer development. Pharmacogenetics, 13(2), 67–72. 10.1097/00008571-200302000-00002 [DOI] [PubMed] [Google Scholar]
- Crabb, D. W. , Edenberg, H. J. , Bosron, W. F. , & Li, T. K. (1989). Genotypes for aldehyde dehydrogenase deficiency and alcohol sensitivity. The inactive ALDH2(2) allele is dominant. Journal of Clinical Investigation, 83(1), 314–316. 10.1172/JCI113875 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Garaycoechea, J. I. , Crossan, G. P. , Langevin, F. , Mulderrig, L. , Louzada, S. , Yang, F. , … Patel, K. J. (2018). Alcohol and endogenous aldehydes damage chromosomes and mutate stem cells. Nature, 553(7687), 171–177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hiraki, A. , Matsuo, K. , Wakai, K. , Suzuki, T. , Hasegawa, Y. , & Tajima, K. (2007). Gene‐gene and gene‐environment interactions between alcohol drinking habit and polymorphisms in alcohol‐metabolizing enzyme genes and the risk of head and neck cancer in Japan. Cancer Science, 98(7), 1087–1091. 10.1111/j.1349-7006.2007.00505.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- IARC Working Group on the Evaluation of Carcinogenic Risks to Humans . (2010). Alcohol consumption and ethyl carbamate. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, 96, 3–1383. [PMC free article] [PubMed] [Google Scholar]
- Ishioka, K. , Masaoka, H. , Ito, H. , Oze, I. , Ito, S. , Tajika, M. , … Matsuo, K. (2018). Association between ALDH2 and ADH1B polymorphisms, alcohol drinking and gastric cancer: A replication and mediation analysis. Gastric Cancer, 21(6), 936–945. 10.1007/s10120-018-0823-0 [DOI] [PubMed] [Google Scholar]
- Kawase, T. , Matsuo, K. , Hiraki, A. , Suzuki, T. , Watanabe, M. , Iwata, H. , … Tajima, K. (2009). Interaction of the effects of alcohol drinking and polymorphisms in alcohol‐metabolizing enzymes on the risk of female breast cancer in Japan. Journal of Epidemiology, 19(5), 244–250. 10.2188/jea.JE20081035 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Li, H. , Borinskaya, S. , Yoshimura, K. , Kal'ina, N. , Marusin, A. , Stepanov, V. A. , … Kidd, K. K. (2009). Refined geographic distribution of the oriental ALDH2*504Lys (nee 487Lys) variant. Annals of Human Genetics, 73(Pt 3), 335–345. 10.1111/j.1469-1809.2009.00517.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- Masaoka, H. , Ito, H. , Soga, N. , Hosono, S. , Oze, I. , Watanabe, M. , … Matsuo, K. (2016). Aldehyde dehydrogenase 2 (ALDH2) and alcohol dehydrogenase 1B (ADH1B) polymorphisms exacerbate bladder cancer risk associated with alcohol drinking: Gene‐environment interaction. Carcinogenesis, 37(6), 583–588. 10.1093/carcin/bgw033 [DOI] [PubMed] [Google Scholar]
- Matsuo, K. , Hamajima, N. , Shinoda, M. , Hatooka, S. , Inoue, M. , Takezaki, T. , & Tajima, K. (2001). Gene‐environment interaction between an aldehyde dehydrogenase‐2 (ALDH2) polymorphism and alcohol consumption for the risk of esophageal cancer. Carcinogenesis, 22(6), 913–916. 10.1093/carcin/22.6.913 [DOI] [PubMed] [Google Scholar]
- Matsuo, K. , Oze, I. , Hosono, S. , Ito, H. , Watanabe, M. , Ishioka, K. , … Tanaka, H. (2013). The aldehyde dehydrogenase 2 (ALDH2) Glu504Lys polymorphism interacts with alcohol drinking in the risk of stomach cancer. Carcinogenesis, 34(7), 1510–1515. 10.1093/carcin/bgt080 [DOI] [PubMed] [Google Scholar]
- Matsuo, K. , Wakai, K. , Hirose, K. , Ito, H. , Saito, T. , & Tajima, K. (2006). Alcohol dehydrogenase 2 His47Arg polymorphism influences drinking habit independently of aldehyde dehydrogenase 2 Glu487Lys polymorphism: Analysis of 2,299 Japanese subjects. Cancer Epidemiology, Biomarkers & Prevention, 15(5), 1009–1013. 10.1158/1055-9965.EPI-05-0911 [DOI] [PubMed] [Google Scholar]
- Michailidou, K. , Hall, P. , Gonzalez‐Neira, A. , Ghoussaini, M. , Dennis, J. , Milne, R. L. , … Easton, D. F. (2013). Large‐scale genotyping identifies 41 new loci associated with breast cancer risk. Nature Genetics, 45(4), 353–361. 10.1038/ng.2563 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Michailidou, K. , Lindstrom, S. , Dennis, J. , Beesley, J. , Hui, S. , Kar, S. , … Easton, D. F. (2017). Association analysis identifies 65 new breast cancer risk loci. Nature, 551(7678), 92–94. 10.1038/nature24284 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Oze, I. , Matsuo, K. , Hosono, S. , Ito, H. , Kawase, T. , Watanabe, M. , … Tanaka, H. (2010). Comparison between self‐reported facial flushing after alcohol consumption and ALDH2 Glu504Lys polymorphism for risk of upper aerodigestive tract cancer in a Japanese population. Cancer Science, 101(8), 1875–1880. 10.1111/j.1349-7006.2010.01599.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sangrajrang, S. , Sato, Y. , Sakamoto, H. , Ohnami, S. , Khuhaprema, T. , & Yoshida, T. (2010). Genetic polymorphisms in folate and alcohol metabolism and breast cancer risk: A case‐control study in Thai women. Breast Cancer Research and Treatment, 123(3), 885–893. 10.1007/s10549-010-0804-4 [DOI] [PubMed] [Google Scholar]
- Singletary, K. W. , & Gapstur, S. M. (2001). Alcohol and breast cancer: Review of epidemiologic and experimental evidence and potential mechanisms. JAMA, 286(17), 2143–2151. 10.1001/jama.286.17.2143 [DOI] [PubMed] [Google Scholar]
- Singletary, K. W. , & McNary, M. Q. (1994). Influence of ethanol intake on mammary gland morphology and cell proliferation in normal and carcinogen‐treated rats. Alcoholism, Clinical and Experimental Research, 18(5), 1261–1266. 10.1111/j.1530-0277.1994.tb00116.x [DOI] [PubMed] [Google Scholar]
- Stolzenberg‐Solomon, R. Z. , Chang, S.‐C. , Leitzmann, M. F. , Johnson, K. A. , Johnson, C. , Buys, S. S. , … Ziegler, R. G. (2006). Folate intake, alcohol use, and postmenopausal breast cancer risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. American Journal of Clinical Nutrition, 83(4), 895–904. 10.1093/ajcn/83.4.895 [DOI] [PubMed] [Google Scholar]
- Zhang, M. H. , Man, H. T. , Zhao, X. D. , Dong, N. , & Ma, S. L. (2014). Estrogen receptor‐positive breast cancer molecular signatures and therapeutic potentials (Review). Biomed Rep, 2(1), 41–52. 10.3892/br.2013.187 [DOI] [PMC free article] [PubMed] [Google Scholar]
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