Interaction of alcohol consumption and genetic variants in alcohol metabolism on all-cause and disease-specific mortality: a cohort study

Interaction of alcohol consumption and genetic variants in alcohol metabolism on all-cause and disease-specific mortality: a cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Interaction of alcohol consumption and genetic variants in alcohol metabolism on all-cause and disease-specific mortality: a cohort study Guangfeng Ruan, Zhaohua Zhu, Han Cen, Yuanyuan Wang, Muhui Zeng, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7648401/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: In studies regarding the association between alcohol consumption and mortality, controversy exists regarding the effects of light to moderate alcohol intake, and no study considered the role of alcohol metabolism related genetic variants in this relationship. Similarly, study investigating impact of alcohol consumption on the relationship between these genetic variations and mortality is also lacking. We therefore investigated the associations of alcohol consumption and alcohol metabolism related genetic variants with all-cause and disease-specific mortality, as well as the multiplicative interaction of alcohol consumption and the genetic variants on mortality. Methods: This prospective cohort study utilized data from the UK Biobank. Restricted cubic splines were used to evaluate the shapes of the associations between alcohol consumption and all-cause and disease-specific mortality. Cox proportional hazards models were used to estimate hazard ratios for associations between alcohol intake and mortality, both before and after stratifying by the genetic variants. Similarly, associations between the genetic variants and mortality were also examined before and after stratifying by alcohol intake. Results: Alcohol consumption had a J-shaped link with all-cause and most disease-specific mortality, except neurological. Similarly, beverage-specific intake showed a J-shaped relationship with all-cause mortality. The rs1229984 variant in ADH1B modifies the associations between alcohol consumption and mortality, resulting in elevated risks of all-cause and disease-specific mortality for individuals without the T allele when compared to carriers. Carriers of the rs1229984 C allele exhibited an increased risk of overall mortality. In stratified analyses, the hazard ratios of the rs1229984 C allele progressively rose from never drinkers to light drinkers, moderate drinkers, and ultimately to heavy drinkers. Conclusion: This study underscores the necessity of curbing excessive alcohol consumption to reduce mortality, particularly among individuals lacking the T allele of rs1229984. Alcohol consumption Genetic variants Mortality Interaction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Alcohol is a major environmental hazard, exerting detrimental effects on various health outcomes including cancer, liver disease, cardiovascular disease, and mental disorders [ 1 ]. It is a major contributor to the global burden of disease, resulting in substantial health care and economic burden [ 2 ]. Alcohol consumption is one of the leading risk factors for mortality, being responsible for 6.8% of deaths in men and 2.2% in women worldwide [ 1 ]. However, although the adverse health effects of excessive alcohol intake are widely accepted, controversy exist regarding the effects of light to moderate alcohol intake [ 2 ]. In addition, different types of alcoholic beverages may also have varying effects on health [ 3 ]. In the alcohol metabolism pathway, ethanol is first oxidized by alcohol dehydrogenase (ADH) into acetaldehyde (ethanal), a toxin and carcinogen, and subsequently oxidized by aldehyde dehydrogenase (ALDH) to produce harmless acetic acid (ethanoic acid) [ 4 ]. The enzymatic activity of ADH and ALDH is subjected to regulation by genetic polymorphisms [ 5 ]. Among polymorphisms, the rs1229984 from alcohol dehydrogenase 1B (class I), beta polypeptide (ADH1B) and rs671 from aldehyde dehydrogenase 2 family member (ALDH2) have been functionally proven to impact alcohol metabolism [ 6 ]. Rs1229984 (C > T) is a missense mutation that replaces arginine with histidine in the mature protein, leading to a significantly elevated ethanol-to-acetaldehyde conversion rate [ 7 ]. Rs671 (G > A) is another nonsynonymous variant that causes a change from glutamic acid to lysine, with carriers of A having a lower ability to clear acetaldehyde [ 7 ]. Regardless of alcohol consumption levels, both rs1229984 and rs671 were discovered to be linked with survival rates, implying a possible genetic influence on mortality [ 8 ]. Given that genetic variants in alcohol metabolism enzymes can influence the processing of alcohol, these genetic differences may result in varying degrees of alcohol-related damage. Consequently, the effects of alcohol consumption on mortality may differ depending on these genetic variants. Moreover, as genetic variants in alcohol metabolism enzymes affecting the elimination of ethanol and acetaldehyde and consequently influencing alcohol-related damage, these variants might have a more pronounced effect in populations with higher alcohol consumption. Therefore, associations between these variants and mortality may vary based on the levels of alcohol consumed. To the best of our knowledge, no study has investigated the interaction of alcohol consumption and genetic variations in alcohol metabolism on mortality. Therefore, this study (Fig. 1 ) aimed to evaluate whether genetic variants in ethanol-metabolizing enzymes act as effect modifiers of the associations of the overall and beverage-specific alcohol consumption with all-cause and disease-specific mortality, as well as the associations between these genetic variants and mortality across different levels of alcohol consumption. Materials and Methods Study population This study is based on data from the UK Biobank, a prospective population-based cohort study that enrolled over 500,000 participants aged 40 to 69 years from 22 different assessment centers across the United Kingdom between 2006 and 2010 [ 9 ]. Sociodemographic, lifestyle, health information, and biological samples of the UK Biobank participants were extensively collected to facilitate health-related research for the benefit of the public. In our study, we excluded participants who: withdrew from the study, did not answer or chose ‘prefer not to answer’ when asked about their alcohol consumption frequency, selected ‘do not know’ or ‘prefer not to answer’ regarding the quantity of alcohol consumption, selected ‘prefer not to answer’ for previous alcohol consumption among current non-drinkers, self-reported as ‘drinkers’ but had their alcohol consumption calculated as 0, had missing genotype information, reported a poor self-rated overall health status, or died during the first year of follow-up (Figure S1 ). In addition to the main analyses, we established four distinct cohorts (S1-S4) for sensitivity analyses: Cohort S1 excluded former drinkers to address potential abstainer bias [ 10 ]. Cohort S2 further excluded never drinkers to address potential healthy drinker bias [ 10 ]. Cohort S3 excluded participants who had been previously diagnosed with diseases (based on hospital admission electronic health records before the baseline) that led to over 100 deaths during follow-up to mitigate reverse causality (details of the participants excluded due to specific diseases are presented in Table S1 ) [ 10 ]. Cohort S4 excluded participants with missing covariate values or those who responded ‘do not know’ to the covariate questions or had missing values regarding the quantity of alcohol consumption to enable a more precise analysis. Exposure assessment Alcohol intake was self-reported at the baseline through a touchscreen questionnaire. Participants were asked to estimate their current alcohol intake frequency (daily or almost daily, three or four times a week, once or twice a week, one to three times a month, special occasions only, never, and prefer not to say). For participants who selected ‘never’ (current non-drinker), an additional question was posed to differentiate between former drinkers and lifelong abstainers. Participants were then queried about their alcohol intake across several beverage categories (red wine, white wine/champagne, beer/cider, spirits, fortified wine, and ‘other’) in an average week for those drinking at least weekly, and average monthly intake for those drinking less frequently. Missing values for the alcohol consumption of a specific beverage type were imputed with the median intake for that beverage, corresponding to the respective drinking frequency. Alcohol consumption was calculated using UK units, where 1 UK unit is approximately equivalent to 8 grams of pure ethanol. The conversion factors for different types of alcoholic beverages were as follows: 1 glass of red or white wine/champagne was equivalent to 1.7 units, 1 pint of beer/cider to 2.4 units, 1 measure of spirits/liqueurs to 1 unit, 1 glass of fortified wine to 1.2 units, and 1 glass of other alcoholic drinks to 1.2 units [ 11 ]. The total number of weekly units was calculated by summing the weekly units consumed in all categories. To estimate a weekly amount for monthly intake, the monthly units were divided by 4.3. In this study, we separated former drinkers from never drinkers, and categorized current drinkers into three groups: light drinkers (≤ 14 units/week), moderate drinkers (14–50 units/week for males, 14–35 units/week for females), and heavy drinkers (> 50 units/week for males, > 35 units/week for females [ 12 ]. Genotyping of the UK Biobank samples was performed using the Affymetrix UK Biobank Axiom array for 67% of the samples and the Affymetrix UK BiLEVE Axiom array for the remaining 33%. Quality control, phasing and imputation of the genotype data are described in detail elsewhere [ 13 ]. Outcome assessment Mortality data were obtained though the National Health Service Information Centre (England and Wales) and the National Health Service Central Register Scotland (Scotland). Records include date of death and primary cause of death, diagnosed in accordance with the tenth edition of the International Classification of Diseases (ICD-10). The follow-up time was calculated from baseline until the first occurrence of either the date of death or December 31, 2021. Statistical analysis The distribution of baseline demographic and health-related characteristics, alcohol consumption, and genotype information were described across the alcohol consumption groups or genotype of alcohol metabolism-related genes, using percentage, mean and standard deviation, and interquartile range where appropriate. Restricted cubic spline (RCS) models with four knots (5th, 35th, 65th, 95th percentiles) were used to evaluate the shapes of the associations between alcohol consumption and mortality. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for the associations between exposures and outcomes with follow-up time as the timescale. Schoenfeld residuals were used to test the proportional hazards assumption. In models with alcohol consumption as the exposure, adjustments were made for age, sex, race, BMI, education, Townsend deprivation index, smoking status, regular physical activity, self-rated overall health, and diabetes. When beverage-specific alcohol consumption was the exposure, other types of beverage consumption were further adjusted. For models with genetic variants as the exposure, adjustments included alcohol intake, age, sex, genotyping batch, and the first 10 principal components of ancestry. Missing data of the covariates were addressed by multiple imputations with chained equations. To test for multiplicative interaction, cross-product terms were added into the Cox models. Stratified analyses were conducted based on genetic variants in models with alcohol consumption as the exposure, and vice versa, based on alcohol consumption in models with genetic variation as the exposure. Sensitivity analyses were conducted in cohort S1-S4, along with an additional competing risk model for disease-specific mortalities in the total population. A P value of < 0.05 was considered as statistically significant in all analyses. Results Participant characteristics Of the total 414,682 participants who were included in the main analyses, the mean age was 56.5 years, and 47.1% were male. Baseline characteristics according to the alcohol consumption groups or genotype of alcohol metabolism-related genes (rs1229984 and rs671) are shown in Table S2 and Table S3, respectively. During a mean 12.6-year follow-up period, there were 27,013 deaths (16,344 in male and 10,669 in female), with 14,130 being cancer-specific mortality, 5,310 being cardiovascular-specific mortality, 1,611 being respiratory-specific mortality, 933 being digestive-specific mortality, 2,576 being neurological-specific mortality, and 1,422 being psychiatric-specific mortality. Associations between alcohol consumption and mortality Restricted cubic splines analyses indicated J-shaped relationships between alcohol intake and all-cause mortality, with the nadir at approximately 13 units/week for all the participants (Fig. 2 ). In sex-dependent analyses, the nadir was around 16 units/week for males and 12 units/week for females (Figure S2 , Figure S3). The HR for a 10-unit/week increase in alcohol intake was 1.020 (95% CI: 1.014, 1.027) for all participants, 1.026 (95% CI: 1.019, 1.033) for males, and 0.983 (95% CI: 0.966, 0.999) for females (Fig. 3 , Table S4). Regarding disease-specific mortalities, all except for neurological-specific mortality, were J-shaped associated with alcohol intake with the nadirs ranging from around 9 to 14 units per week (Fig. 2 ). The risk of neurological-specific mortality, however, appears to decrease continuously with increased alcohol intake (Fig. 2 ). When investigating gender differences, the dose-response curves indicate that females appear to be less likely to benefit from light to moderate drinking (Figure S2 , Figure S3). The inflection point of the J-shaped curve of alcohol intake with overall mortality is close to the cutoff for light and moderate drinking. Considering that the correlation curve closely approximates linearity on both sides of the inflection point, we also separately calculated the HRs for overall and disease-specific mortality associated with alcohol intake in non-drinkers and light drinkers (Figure S4), as well as in moderate and heavy drinkers (Figure S5). In terms of beverage-specific alcohol consumption, although all types of beverage consumption exhibited a J-shaped association with all-cause mortality, the overall HRs varied (Fig. 4 ). HRs for spirits/liqueurs, fortified wine, and beer/cider were greater than 1, whereas the HRs for white wine/champagne and red wine were less than 1. The study also examined the association between different types of beverage consumption and disease-specific mortality, revealing diverse dose-response curves (Figure S6, Figure S7). Our sensitivity analysis on overall and beverage-specific alcohol consumption in relation to all-cause and disease-specific mortality yielded results similar to our main analysis, both for the entire cohort and when analyzed separately for males and females (Table S5-9). Associations of alcohol consumption with mortality stratified by alcohol metabolism-related genes Multiplicative interaction analyses prompt that rs1229984 ( P for interaction = 0.003) but not rs671 ( P for interaction = 0.675) is a modifier of the associations between the overall alcohol consumption and all-cause mortality. Stratified analysis by rs1229984 reveals that the risk of total mortality and disease-specific mortality due to alcohol consumption is consistently higher among individuals with the CC genotype when compared to those with the CT or TT genotypes (Fig. 5 ). The stratified analyses were also conducted separately among males and females (Table S10), as well as among non-light drinkers and moderate-heavy drinkers (Table S11). The association of beverage-specific alcohol consumption with all-cause and disease-specific mortality, stratified by rs1229984, was presented in Table S12. In sensitivity analysis, the modification effect of rs1229984 was also observed on the association between alcohol consumption and mortality (Table S13). The relationship of alcohol metabolism-related genes with mortality and the results stratified by alcohol consumption Carriers of the rs1229984 C allele were significantly associated with increased overall mortality (Fig. 6 ). Similar results were found for all disease-specific mortalities, although statistical significance was observed only in the case of cardiovascular-specific mortality (Fig. 6 ). Results of multiplicative interaction suggest that the association between rs1229984 and all-cause mortality, cardiovascular-specific mortality, as well as digestive-specific disease mortality could be modified by alcohol consumption (<0.001, 0.001, 0.034 for P for interaction respectively). In stratified analyses, the risks associated with rs1229984 for all-cause, cardiovascular-specific, and digestive-specific disease mortality gradually increased from never drinkers to light drinkers, moderate drinkers, and finally to heavy drinkers (Fig. 6 ). We did not identify any significant associations between rs671 and either all-cause mortality or disease-specific mortality (Table S14). In sensitivity analysis, we found results consistent with the main analysis (Table S15-18). Discussion In this study, we found that both alcohol consumption and genotype of rs1229984 from ADH1B, were significantly associated with overall and disease-specific mortality. Importantly, multiplicative interaction was identified between alcohol consumption and rs1229984 on mortality, that is, alcohol consumption can modify the influence of rs1229984 on mortality; and also, the rs1229984 acts as a modifier for the associations between alcohol consumption and mortality. Similar to previous studies [ 12 , 14 – 16 ], a J-shaped relationship was observed between alcohol consumption and mortality in our study. The J-shaped association has been challenged recently in light of methodological concerns regarding potential selection biases and residual confounding [ 10 , 17 ]. Nevertheless, we strive to mitigate potential biases, such as the ‘abstainer’ bias, ‘healthy drinker’ bias, reverse causation, and confounding, in our analysis. However, it’s essential to recognize that, due to the nature of observational studies, these biases may not be entirely eliminated. When examining the association between alcohol consumption and disease-specific mortality, J-shaped curves with varying magnitudes were observed for most of the disease-specific mortalities, with the exception of neurological-specific mortality. We conjectured that the inverse relationship between alcohol consumption and neurological-specific mortality could be attributed to reverse causality, as individuals diagnosed with neurological diseases may reduce or cease alcohol consumption. However, in sensitivity analysis excluding participants diagnosed with major neurological disease at baseline, similar result was still yielded, which do not support the reverse causal hypothesis. An alternative explanation could be that the observed inverse relationship between alcohol consumption and neurological-specific mortality is due to the possibility that individuals who did not die because of neurological diseases may have perished from other health conditions [ 18 ]. However, when considering competing risks of mortality in our analysis, we found result similar to that in the main analysis, enhancing our confidence in the robustness of our primary findings. When conducting a detailed investigation into the relationship between different types of beverages and mortality, we observed variations in the shape, magnitude, and nadir of the association curves across different beverage categories. In our study, light to moderate consumption of wine, especially red wine can reduce overall mortality. The health benefits of wine are likely predominantly attributed to the polyphenols it contains, as these compounds exhibit antioxidant, anticarcinogenic, anti-inflammatory, hypotensive, and even anticoagulant properties (red wine contains approximately 10 times more polyphenols than white wine) [ 3 ]. Our research suggests that light beer consumption may also have a slight protective effect against all-cause mortality. This could be due to the bioactive compounds in beer with antioxidant and anti-inflammatory activity, although the polyphenol content in beer is relatively low [ 3 ]. However, spirits/liqueurs and fortified wine tend to linearly increase overall mortality, despite small amounts of these alcoholic beverages may result in a slight reduction in overall mortality. Alcohol could be the key factor driving the detrimental effects of these beverages, even though moderate alcohol intake may have benefit effect on cholesterol concentrations, insulin sensitivity, platelet aggregation, and blood clotting [ 19 ]. In our analysis of the impact of different beverages on disease-specific mortality, we have observed variations in the dose-response curves between specific beverages and the risk of disease-specific mortality, which could reflect the complexity of the effects of alcoholic beverages on health. For instance, in the case of cancer-specific mortality, beer/cider consumption is associated with an increased mortality risk, whereas white wine/champagne consumption may somewhat reduce the risk; however, for respiratory-specific mortality, beer/cider exhibits a protective effect similar to that of white wine/champagne. Notably, this study revealed significant multiplicative interactions between genetic variants in alcohol metabolism enzymes and alcohol consumption in relation to mortality, for the first time to our knowledge. In the stratified analysis, participants with the CT or TT genotype of rs1229984 demonstrated lower HRs for alcohol consumption on all-cause mortality and all the disease-specific mortalities when compared to those with the CC genotype. CC genotype of rs1229984 results in low catalytic activity of ADH1B, leading to the slow metabolism of alcohol to acetaldehyde in the body [ 4 , 20 ]. This finding suggests that alcohol intake could be more harmful to individuals with the CC genotype of rs1229984, indicating that slow conversion of ethanol into acetaldehyde in the body could be disadvantageous for health. Carriers of the rs671 A allele are linked to decreased ALDH2 activity, which results in a reduced ability to clear acetaldehyde [ 7 ]. Previous research has revealed that among individuals with a rapid ethanol oxidation rate, those carrying the AG genotype of rs671 had a higher risk of esophageal squamous cell cancer associated with alcohol consumption compared to those with the GG genotype [ 4 ]. In our study, we did not observe a significant interaction between rs671 and alcohol consumption concerning mortality. This lack of significance may be attributed to the relatively low frequency of the A allele of rs671 among the European participants on whom we concentrated. This study has identified significant associations between the rs1229984 genotype and mortality, whereas no such associations were found for rs671. It has been reported that the amount of alcohol consumed varies among individuals with different polymorphisms related to alcohol metabolism, which is potentially attributed to altered acetaldehyde accumulation rates affecting the pleasure of drinking [ 4 , 19 ]. This study aims to explore the associations of genetic variants with mortality that are not mediated by the amount of alcohol individuals consume; therefore, alcohol consumption was controlled in our analyses to eliminate its potential mediating effect. In the Japanese population, both rs1229984 and rs671 were found to be associated with all-cause mortality, independent of alcohol consumption [ 8 ]. The absence of statistical significance for rs671 in our study can likely be attributed to its infrequent polymorphism occurrence, with the exception being among East Asians [ 8 ]. Moreover, alcohol intake was recognized as a modifier for the relationship between rs1229984 and mortality. When stratified by alcohol consumption, HRs for all-cause, cardiovascular-specific, and digestive-specific disease mortality exhibited a gradual increase from never drinkers to heavy drinkers. This corroborates our conjecture that increased alcohol consumption amplifies the ethanol buildup due to the lowly active ADH1B, thereby magnifying the impact of rs1229984 on health. In our study, we found no association between rs1229984 and overall mortality in individuals who never drank alcohol. This implies that rs1229984 may primarily affect health by influencing alcohol metabolism, although prior studies report associations of rs1229984 with body mass index and pulse pressure [ 21 , 22 ]. This study demonstrates several strengths, including its prospective cohort design, a large sample size, a long-term follow-up period, and a thorough investigation into beverage-specific alcohol consumption and disease-specific mortality. Several limitations of this study should also be acknowledged. Firstly, alcohol consumption was self-reported, although this is common in large population-based studies, the possibility of measurement bias should be recognized. Secondly, alcohol consumption was ascertained at baseline, and it’s possible that participants’ drinking habits may have changed during the follow-up period. Thirdly, although we adjusted for multi-dimensional confounders, residual confounding cannot be completely ruled out due to the observational nature of the study. Fourthly, the frequency of the rs671 polymorphism is low in the European population we studied. Significant results may be found for rs671 in populations with a higher frequency of the rs671 polymorphism, such as the Asian population. Conclusions In conclusion, overall and beverage-specific alcohol consumption exhibit a J-shaped association with all-cause mortality, although some variations exist in the dose-response curves for disease-specific mortality. Moreover, the C allele of rs1229984 in ADH1B is associated with increased risk of mortality. Notably, a multiplicative interaction exists between alcohol consumption and rs1229984 for mortality, highlighting a higher risk of excessive alcohol use in individuals harboring the variant associated with low ADH1B activity. Declarations Acknowledgements The authors extend their gratitude to all participants of the UK Biobank. Author contributions Drs Changhai Ding and Yan Zhang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: Changhai Ding, Yan Zhang. Acquisition, analysis, or interpretation of data: Guangfeng Ruan, Zhaohua Zhu, Han Cen, Yuanyuan Wang, Muhui Zeng, Xizeng Zong, Jie Wang, Xingzhong Jin, Simin Wen, Siqi Xu. Drafting of the manuscript: Guangfeng Ruan, Zhaohua Zhu, Han Cen, Yuanyuan Wang. Obtained funding: Guangfeng Ruan, Zhaohua Zhu, Yuanyuan Wang, Changhai Ding, Yan Zhang. Administrative, technical, or material support: Qian Yang, Yujie Zhang. Supervision: Yan Zhang, Changhai Ding. All authors have read, revised and approved the final manuscript. Funding This work has been fully supported by the Guangdong Basic and Applied Basic Research Foundation (2023A1515011518), the National Natural Science Foundation of China (82373653 & 82472478), the Science and Technology Program of Guangzhou (2025A04J3955), the President Foundation of Nanfang Hospital, Southern Medical University (2021C006), and the Zhujiang Hospital Talent Recruitment Funds and Clinical Research Startup Program of Southern Medical University (no. LC2019ZD015). Data availability statement Publicly available data from the UK Biobank study was analyzed in this study. The datasets are available to researchers through an open application via https://www.ukbiobank.ac.uk/use-our-data/apply-for-access/. Ethics approval and consent to participate The studies were carried out in accordance with the Helsinki Declaration of 1975 as revised in 1983.The UK Biobank data were approved by the North West Multi-centre Research Ethics Committee (MREC) (REC reference: 16/NW/0274). Additionally, our institution, Guangzhou First People's Hospital, has granted an ethical approval exemption (K-2025-028-01). Consent for publication All participants provided written informed consent. Competing interests The authors declare no conflict of interest. Patient and public involvement statement Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research. References Sinn DH, Kang D, Guallar E, et al. Alcohol Intake and Mortality in Patients With Chronic Viral Hepatitis: A Nationwide Cohort Study. Am J Gastroenterol. 2021;116(2):329–35. Xi B, Veeranki SP, Zhao M, Ma C, Yan Y, Mi J. 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Supplementary Files SupplementaryTables.doc Table S1 Number of the participants diagnosed with diseases that cause over 100 deaths during follow-up Table S2 Baseline characteristics according to alcohol consumption status Table S3 Baseline characteristics according to genotype of rs1229984 and rs671 Table S4 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in main analysis Table S5 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S1 Table S6 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S2 Table S7 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S3 Table S8 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S4 Table S9 Hazard ratios for total and beverage-specific alcohol consumption on cause-specific mortality before and after stratifying by sex in competing risk model Table S10 Hazard ratios for alcohol consumption on all-cause and cause-specific mortality stratifying by rs1229984 in male and female Table S11 Hazard ratios for alcohol consumption on all-cause and cause-specific mortality stratifying by rs1229984 in non-light drinker and moderate-heavy drinkers Table S12 Hazard ratios for beverage-specific alcohol consumption on all-cause and disease-specific mortality stratifying by rs1229984 Table S13 Hazard ratios for alcohol consumption on all-cause and disease-specific mortality stratifying by rs1229984 in cohort S1-S4 and competing risk model Table S14 Associations of rs671 with all-cause and disease-specific mortality Table S15 Hazard ratios for rs1229984 on all-cause and disease-specific mortality before and after stratifying by alcohol consumption in cohort S1 and S2 Table S16 Hazard ratios for rs1229984 on all-cause and disease-specific mortality before and after stratifying by alcohol consumption in cohort S3 Table S17 Hazard ratios for rs1229984 on all-cause and disease-specific mortality before and after stratifying by alcohol consumption in cohort S4 Table S18 Hazard ratios for rs1229984 on disease-specific mortality before and after stratifying by alcohol consumption in competing risk model SupplementaryFigures.doc Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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16:53:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1093538,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRestricted cubic splines and forest plot for the associations between beverage-specific alcohol consumption and all-cause mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Restricted cubic splines for the associations between beverage-specific alcohol consumption and all-cause mortality; (B) Hazard ratios for the associations between beverage-specific alcohol consumption (10-unit/week) and all-cause mortality.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7648401/v1/04db28bdbdeecc4fd11b7833.png"},{"id":95222257,"identity":"6868b864-237c-4940-a536-be0fc2c77071","added_by":"auto","created_at":"2025-11-05 16:20:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":204435,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHazard ratios for the associations of alcohol consumption with all-cause and disease-specific mortality stratifying by rs1229984\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Hazard ratios were for peer 10-unit/week of alcohol consumption.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7648401/v1/d6ac41cc048816bccfc75f91.png"},{"id":95222159,"identity":"c3b4082c-a968-4d6d-aeec-b03b823ee794","added_by":"auto","created_at":"2025-11-05 16:20:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":324209,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHazard ratios for the associations of rs1229984 with all-cause and disease-specific mortality before and after stratifying by alcohol consumption\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7648401/v1/ef364bd6d41cdd517550832b.png"},{"id":109581788,"identity":"5926a07b-ef42-4466-9104-0d27bec7ae27","added_by":"auto","created_at":"2026-05-19 19:55:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7394055,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7648401/v1/fc661d79-7303-472b-ac10-4373e2d6f5a2.pdf"},{"id":95222915,"identity":"a5edf2ad-05da-44e4-a38a-a34cf732015d","added_by":"auto","created_at":"2025-11-05 16:21:20","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":457216,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S1 Number of the participants diagnosed with diseases that cause over 100 deaths during follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S2 Baseline characteristics according to alcohol consumption status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S3 Baseline characteristics according to genotype of rs1229984 and rs671\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S4 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in main analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S5 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S6 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S7 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S8 Hazard ratios for total and beverage-specific alcohol consumption on all-cause and cause-specific mortality before and after stratifying by sex in cohort S4\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S9 Hazard ratios for total and beverage-specific alcohol consumption on cause-specific mortality before and after stratifying by sex in competing risk model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S10 Hazard ratios for alcohol consumption on all-cause and cause-specific mortality stratifying by rs1229984 in male and female\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S11 Hazard ratios for alcohol consumption on all-cause and cause-specific mortality stratifying by rs1229984 in non-light drinker and moderate-heavy drinkers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S12 Hazard ratios for beverage-specific alcohol consumption on all-cause and disease-specific mortality stratifying by rs1229984\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S13 Hazard ratios for alcohol consumption on all-cause and disease-specific mortality stratifying by rs1229984 in cohort S1-S4 and competing risk model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S14 Associations of rs671 with all-cause and disease-specific mortality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S15 Hazard ratios for rs1229984 on all-cause and disease-specific mortality before and after stratifying by alcohol consumption in cohort S1 and S2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S16 Hazard ratios for rs1229984 on all-cause and disease-specific mortality before and after stratifying by alcohol consumption in cohort S3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S17 Hazard ratios for rs1229984 on all-cause and disease-specific mortality before and after stratifying by alcohol consumption in cohort S4\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S18 Hazard ratios for rs1229984 on disease-specific mortality before and after stratifying by alcohol consumption in competing risk model\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryTables.doc","url":"https://assets-eu.researchsquare.com/files/rs-7648401/v1/68027d6d8ee7358e30153cf1.doc"},{"id":95045414,"identity":"291d6970-ad2f-4873-a10c-096c5b2ae3f8","added_by":"auto","created_at":"2025-11-03 16:53:41","extension":"doc","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10576384,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.doc","url":"https://assets-eu.researchsquare.com/files/rs-7648401/v1/fa0ca3dd886a0835d2da965f.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Interaction of alcohol consumption and genetic variants in alcohol metabolism on all-cause and disease-specific mortality: a cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlcohol is a major environmental hazard, exerting detrimental effects on various health outcomes including cancer, liver disease, cardiovascular disease, and mental disorders [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is a major contributor to the global burden of disease, resulting in substantial health care and economic burden [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Alcohol consumption is one of the leading risk factors for mortality, being responsible for 6.8% of deaths in men and 2.2% in women worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, although the adverse health effects of excessive alcohol intake are widely accepted, controversy exist regarding the effects of light to moderate alcohol intake [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In addition, different types of alcoholic beverages may also have varying effects on health [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the alcohol metabolism pathway, ethanol is first oxidized by alcohol dehydrogenase (ADH) into acetaldehyde (ethanal), a toxin and carcinogen, and subsequently oxidized by aldehyde dehydrogenase (ALDH) to produce harmless acetic acid (ethanoic acid) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The enzymatic activity of ADH and ALDH is subjected to regulation by genetic polymorphisms [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Among polymorphisms, the rs1229984 from alcohol dehydrogenase 1B (class I), beta polypeptide (ADH1B) and rs671 from aldehyde dehydrogenase 2 family member (ALDH2) have been functionally proven to impact alcohol metabolism [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Rs1229984 (C\u0026thinsp;\u0026gt;\u0026thinsp;T) is a missense mutation that replaces arginine with histidine in the mature protein, leading to a significantly elevated ethanol-to-acetaldehyde conversion rate [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Rs671 (G\u0026thinsp;\u0026gt;\u0026thinsp;A) is another nonsynonymous variant that causes a change from glutamic acid to lysine, with carriers of A having a lower ability to clear acetaldehyde [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Regardless of alcohol consumption levels, both rs1229984 and rs671 were discovered to be linked with survival rates, implying a possible genetic influence on mortality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven that genetic variants in alcohol metabolism enzymes can influence the processing of alcohol, these genetic differences may result in varying degrees of alcohol-related damage. Consequently, the effects of alcohol consumption on mortality may differ depending on these genetic variants. Moreover, as genetic variants in alcohol metabolism enzymes affecting the elimination of ethanol and acetaldehyde and consequently influencing alcohol-related damage, these variants might have a more pronounced effect in populations with higher alcohol consumption. Therefore, associations between these variants and mortality may vary based on the levels of alcohol consumed.\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, no study has investigated the interaction of alcohol consumption and genetic variations in alcohol metabolism on mortality. Therefore, this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) aimed to evaluate whether genetic variants in ethanol-metabolizing enzymes act as effect modifiers of the associations of the overall and beverage-specific alcohol consumption with all-cause and disease-specific mortality, as well as the associations between these genetic variants and mortality across different levels of alcohol consumption.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eThis study is based on data from the UK Biobank, a prospective population-based cohort study that enrolled over 500,000 participants aged 40 to 69 years from 22 different assessment centers across the United Kingdom between 2006 and 2010 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Sociodemographic, lifestyle, health information, and biological samples of the UK Biobank participants were extensively collected to facilitate health-related research for the benefit of the public. In our study, we excluded participants who: withdrew from the study, did not answer or chose \u0026lsquo;prefer not to answer\u0026rsquo; when asked about their alcohol consumption frequency, selected \u0026lsquo;do not know\u0026rsquo; or \u0026lsquo;prefer not to answer\u0026rsquo; regarding the quantity of alcohol consumption, selected \u0026lsquo;prefer not to answer\u0026rsquo; for previous alcohol consumption among current non-drinkers, self-reported as \u0026lsquo;drinkers\u0026rsquo; but had their alcohol consumption calculated as 0, had missing genotype information, reported a poor self-rated overall health status, or died during the first year of follow-up (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In addition to the main analyses, we established four distinct cohorts (S1-S4) for sensitivity analyses: Cohort S1 excluded former drinkers to address potential abstainer bias [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Cohort S2 further excluded never drinkers to address potential healthy drinker bias [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Cohort S3 excluded participants who had been previously diagnosed with diseases (based on hospital admission electronic health records before the baseline) that led to over 100 deaths during follow-up to mitigate reverse causality (details of the participants excluded due to specific diseases are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Cohort S4 excluded participants with missing covariate values or those who responded \u0026lsquo;do not know\u0026rsquo; to the covariate questions or had missing values regarding the quantity of alcohol consumption to enable a more precise analysis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExposure assessment\u003c/h3\u003e\n\u003cp\u003eAlcohol intake was self-reported at the baseline through a touchscreen questionnaire. Participants were asked to estimate their current alcohol intake frequency (daily or almost daily, three or four times a week, once or twice a week, one to three times a month, special occasions only, never, and prefer not to say). For participants who selected \u0026lsquo;never\u0026rsquo; (current non-drinker), an additional question was posed to differentiate between former drinkers and lifelong abstainers. Participants were then queried about their alcohol intake across several beverage categories (red wine, white wine/champagne, beer/cider, spirits, fortified wine, and \u0026lsquo;other\u0026rsquo;) in an average week for those drinking at least weekly, and average monthly intake for those drinking less frequently. Missing values for the alcohol consumption of a specific beverage type were imputed with the median intake for that beverage, corresponding to the respective drinking frequency. Alcohol consumption was calculated using UK units, where 1 UK unit is approximately equivalent to 8 grams of pure ethanol. The conversion factors for different types of alcoholic beverages were as follows: 1 glass of red or white wine/champagne was equivalent to 1.7 units, 1 pint of beer/cider to 2.4 units, 1 measure of spirits/liqueurs to 1 unit, 1 glass of fortified wine to 1.2 units, and 1 glass of other alcoholic drinks to 1.2 units [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The total number of weekly units was calculated by summing the weekly units consumed in all categories. To estimate a weekly amount for monthly intake, the monthly units were divided by 4.3. In this study, we separated former drinkers from never drinkers, and categorized current drinkers into three groups: light drinkers (\u0026le;\u0026thinsp;14 units/week), moderate drinkers (14\u0026ndash;50 units/week for males, 14\u0026ndash;35 units/week for females), and heavy drinkers (\u0026gt;\u0026thinsp;50 units/week for males, \u0026gt;\u0026thinsp;35 units/week for females [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGenotyping of the UK Biobank samples was performed using the Affymetrix UK Biobank Axiom array for 67% of the samples and the Affymetrix UK BiLEVE Axiom array for the remaining 33%. Quality control, phasing and imputation of the genotype data are described in detail elsewhere [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOutcome assessment\u003c/h3\u003e\n\u003cp\u003eMortality data were obtained though the National Health Service Information Centre (England and Wales) and the National Health Service Central Register Scotland (Scotland). Records include date of death and primary cause of death, diagnosed in accordance with the tenth edition of the International Classification of Diseases (ICD-10). The follow-up time was calculated from baseline until the first occurrence of either the date of death or December 31, 2021.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eThe distribution of baseline demographic and health-related characteristics, alcohol consumption, and genotype information were described across the alcohol consumption groups or genotype of alcohol metabolism-related genes, using percentage, mean and standard deviation, and interquartile range where appropriate.\u003c/p\u003e\u003cp\u003eRestricted cubic spline (RCS) models with four knots (5th, 35th, 65th, 95th percentiles) were used to evaluate the shapes of the associations between alcohol consumption and mortality. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) for the associations between exposures and outcomes with follow-up time as the timescale. Schoenfeld residuals were used to test the proportional hazards assumption. In models with alcohol consumption as the exposure, adjustments were made for age, sex, race, BMI, education, Townsend deprivation index, smoking status, regular physical activity, self-rated overall health, and diabetes. When beverage-specific alcohol consumption was the exposure, other types of beverage consumption were further adjusted. For models with genetic variants as the exposure, adjustments included alcohol intake, age, sex, genotyping batch, and the first 10 principal components of ancestry. Missing data of the covariates were addressed by multiple imputations with chained equations. To test for multiplicative interaction, cross-product terms were added into the Cox models. Stratified analyses were conducted based on genetic variants in models with alcohol consumption as the exposure, and vice versa, based on alcohol consumption in models with genetic variation as the exposure. Sensitivity analyses were conducted in cohort S1-S4, along with an additional competing risk model for disease-specific mortalities in the total population. A \u003cem\u003eP\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05 was considered as statistically significant in all analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eParticipant characteristics\u003c/h2\u003e\u003cp\u003eOf the total 414,682 participants who were included in the main analyses, the mean age was 56.5 years, and 47.1% were male. Baseline characteristics according to the alcohol consumption groups or genotype of alcohol metabolism-related genes (rs1229984 and rs671) are shown in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e and Table S3, respectively. During a mean 12.6-year follow-up period, there were 27,013 deaths (16,344 in male and 10,669 in female), with 14,130 being cancer-specific mortality, 5,310 being cardiovascular-specific mortality, 1,611 being respiratory-specific mortality, 933 being digestive-specific mortality, 2,576 being neurological-specific mortality, and 1,422 being psychiatric-specific mortality.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssociations between alcohol consumption and mortality\u003c/h3\u003e\n\u003cp\u003eRestricted cubic splines analyses indicated J-shaped relationships between alcohol intake and all-cause mortality, with the nadir at approximately 13 units/week for all the participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In sex-dependent analyses, the nadir was around 16 units/week for males and 12 units/week for females (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, Figure S3). The HR for a 10-unit/week increase in alcohol intake was 1.020 (95% CI: 1.014, 1.027) for all participants, 1.026 (95% CI: 1.019, 1.033) for males, and 0.983 (95% CI: 0.966, 0.999) for females (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding disease-specific mortalities, all except for neurological-specific mortality, were J-shaped associated with alcohol intake with the nadirs ranging from around 9 to 14 units per week (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The risk of neurological-specific mortality, however, appears to decrease continuously with increased alcohol intake (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When investigating gender differences, the dose-response curves indicate that females appear to be less likely to benefit from light to moderate drinking (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e, Figure S3).\u003c/p\u003e\u003cp\u003eThe inflection point of the J-shaped curve of alcohol intake with overall mortality is close to the cutoff for light and moderate drinking. Considering that the correlation curve closely approximates linearity on both sides of the inflection point, we also separately calculated the HRs for overall and disease-specific mortality associated with alcohol intake in non-drinkers and light drinkers (Figure S4), as well as in moderate and heavy drinkers (Figure S5).\u003c/p\u003e\u003cp\u003eIn terms of beverage-specific alcohol consumption, although all types of beverage consumption exhibited a J-shaped association with all-cause mortality, the overall HRs varied (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). HRs for spirits/liqueurs, fortified wine, and beer/cider were greater than 1, whereas the HRs for white wine/champagne and red wine were less than 1. The study also examined the association between different types of beverage consumption and disease-specific mortality, revealing diverse dose-response curves (Figure S6, Figure S7).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOur sensitivity analysis on overall and beverage-specific alcohol consumption in relation to all-cause and disease-specific mortality yielded results similar to our main analysis, both for the entire cohort and when analyzed separately for males and females (Table S5-9).\u003c/p\u003e\n\u003ch3\u003eAssociations of alcohol consumption with mortality stratified by alcohol metabolism-related genes\u003c/h3\u003e\n\u003cp\u003eMultiplicative interaction analyses prompt that rs1229984 (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.003) but not rs671 (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.675) is a modifier of the associations between the overall alcohol consumption and all-cause mortality. Stratified analysis by rs1229984 reveals that the risk of total mortality and disease-specific mortality due to alcohol consumption is consistently higher among individuals with the CC genotype when compared to those with the CT or TT genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The stratified analyses were also conducted separately among males and females (Table S10), as well as among non-light drinkers and moderate-heavy drinkers (Table S11). The association of beverage-specific alcohol consumption with all-cause and disease-specific mortality, stratified by rs1229984, was presented in Table S12. In sensitivity analysis, the modification effect of rs1229984 was also observed on the association between alcohol consumption and mortality (Table S13).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eThe relationship of alcohol metabolism-related genes with mortality and the results stratified by alcohol consumption\u003c/h2\u003e\u003cp\u003eCarriers of the rs1229984 C allele were significantly associated with increased overall mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Similar results were found for all disease-specific mortalities, although statistical significance was observed only in the case of cardiovascular-specific mortality (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Results of multiplicative interaction suggest that the association between rs1229984 and all-cause mortality, cardiovascular-specific mortality, as well as digestive-specific disease mortality could be modified by alcohol consumption (\u0026lt;0.001, 0.001, 0.034 for \u003cem\u003eP\u003c/em\u003e for interaction respectively). In stratified analyses, the risks associated with rs1229984 for all-cause, cardiovascular-specific, and digestive-specific disease mortality gradually increased from never drinkers to light drinkers, moderate drinkers, and finally to heavy drinkers (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). We did not identify any significant associations between rs671 and either all-cause mortality or disease-specific mortality (Table S14). In sensitivity analysis, we found results consistent with the main analysis (Table S15-18).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we found that both alcohol consumption and genotype of rs1229984 from ADH1B, were significantly associated with overall and disease-specific mortality. Importantly, multiplicative interaction was identified between alcohol consumption and rs1229984 on mortality, that is, alcohol consumption can modify the influence of rs1229984 on mortality; and also, the rs1229984 acts as a modifier for the associations between alcohol consumption and mortality.\u003c/p\u003e\u003cp\u003eSimilar to previous studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], a J-shaped relationship was observed between alcohol consumption and mortality in our study. The J-shaped association has been challenged recently in light of methodological concerns regarding potential selection biases and residual confounding [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Nevertheless, we strive to mitigate potential biases, such as the \u0026lsquo;abstainer\u0026rsquo; bias, \u0026lsquo;healthy drinker\u0026rsquo; bias, reverse causation, and confounding, in our analysis. However, it\u0026rsquo;s essential to recognize that, due to the nature of observational studies, these biases may not be entirely eliminated. When examining the association between alcohol consumption and disease-specific mortality, J-shaped curves with varying magnitudes were observed for most of the disease-specific mortalities, with the exception of neurological-specific mortality. We conjectured that the inverse relationship between alcohol consumption and neurological-specific mortality could be attributed to reverse causality, as individuals diagnosed with neurological diseases may reduce or cease alcohol consumption. However, in sensitivity analysis excluding participants diagnosed with major neurological disease at baseline, similar result was still yielded, which do not support the reverse causal hypothesis. An alternative explanation could be that the observed inverse relationship between alcohol consumption and neurological-specific mortality is due to the possibility that individuals who did not die because of neurological diseases may have perished from other health conditions [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, when considering competing risks of mortality in our analysis, we found result similar to that in the main analysis, enhancing our confidence in the robustness of our primary findings.\u003c/p\u003e\u003cp\u003eWhen conducting a detailed investigation into the relationship between different types of beverages and mortality, we observed variations in the shape, magnitude, and nadir of the association curves across different beverage categories. In our study, light to moderate consumption of wine, especially red wine can reduce overall mortality. The health benefits of wine are likely predominantly attributed to the polyphenols it contains, as these compounds exhibit antioxidant, anticarcinogenic, anti-inflammatory, hypotensive, and even anticoagulant properties (red wine contains approximately 10 times more polyphenols than white wine) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Our research suggests that light beer consumption may also have a slight protective effect against all-cause mortality. This could be due to the bioactive compounds in beer with antioxidant and anti-inflammatory activity, although the polyphenol content in beer is relatively low [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, spirits/liqueurs and fortified wine tend to linearly increase overall mortality, despite small amounts of these alcoholic beverages may result in a slight reduction in overall mortality. Alcohol could be the key factor driving the detrimental effects of these beverages, even though moderate alcohol intake may have benefit effect on cholesterol concentrations, insulin sensitivity, platelet aggregation, and blood clotting [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In our analysis of the impact of different beverages on disease-specific mortality, we have observed variations in the dose-response curves between specific beverages and the risk of disease-specific mortality, which could reflect the complexity of the effects of alcoholic beverages on health. For instance, in the case of cancer-specific mortality, beer/cider consumption is associated with an increased mortality risk, whereas white wine/champagne consumption may somewhat reduce the risk; however, for respiratory-specific mortality, beer/cider exhibits a protective effect similar to that of white wine/champagne.\u003c/p\u003e\u003cp\u003eNotably, this study revealed significant multiplicative interactions between genetic variants in alcohol metabolism enzymes and alcohol consumption in relation to mortality, for the first time to our knowledge. In the stratified analysis, participants with the CT or TT genotype of rs1229984 demonstrated lower HRs for alcohol consumption on all-cause mortality and all the disease-specific mortalities when compared to those with the CC genotype. CC genotype of rs1229984 results in low catalytic activity of ADH1B, leading to the slow metabolism of alcohol to acetaldehyde in the body [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This finding suggests that alcohol intake could be more harmful to individuals with the CC genotype of rs1229984, indicating that slow conversion of ethanol into acetaldehyde in the body could be disadvantageous for health. Carriers of the rs671 A allele are linked to decreased ALDH2 activity, which results in a reduced ability to clear acetaldehyde [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Previous research has revealed that among individuals with a rapid ethanol oxidation rate, those carrying the AG genotype of rs671 had a higher risk of esophageal squamous cell cancer associated with alcohol consumption compared to those with the GG genotype [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In our study, we did not observe a significant interaction between rs671 and alcohol consumption concerning mortality. This lack of significance may be attributed to the relatively low frequency of the A allele of rs671 among the European participants on whom we concentrated.\u003c/p\u003e\u003cp\u003eThis study has identified significant associations between the rs1229984 genotype and mortality, whereas no such associations were found for rs671. It has been reported that the amount of alcohol consumed varies among individuals with different polymorphisms related to alcohol metabolism, which is potentially attributed to altered acetaldehyde accumulation rates affecting the pleasure of drinking [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This study aims to explore the associations of genetic variants with mortality that are not mediated by the amount of alcohol individuals consume; therefore, alcohol consumption was controlled in our analyses to eliminate its potential mediating effect. In the Japanese population, both rs1229984 and rs671 were found to be associated with all-cause mortality, independent of alcohol consumption [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The absence of statistical significance for rs671 in our study can likely be attributed to its infrequent polymorphism occurrence, with the exception being among East Asians [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Moreover, alcohol intake was recognized as a modifier for the relationship between rs1229984 and mortality. When stratified by alcohol consumption, HRs for all-cause, cardiovascular-specific, and digestive-specific disease mortality exhibited a gradual increase from never drinkers to heavy drinkers. This corroborates our conjecture that increased alcohol consumption amplifies the ethanol buildup due to the lowly active ADH1B, thereby magnifying the impact of rs1229984 on health. In our study, we found no association between rs1229984 and overall mortality in individuals who never drank alcohol. This implies that rs1229984 may primarily affect health by influencing alcohol metabolism, although prior studies report associations of rs1229984 with body mass index and pulse pressure [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study demonstrates several strengths, including its prospective cohort design, a large sample size, a long-term follow-up period, and a thorough investigation into beverage-specific alcohol consumption and disease-specific mortality. Several limitations of this study should also be acknowledged. Firstly, alcohol consumption was self-reported, although this is common in large population-based studies, the possibility of measurement bias should be recognized. Secondly, alcohol consumption was ascertained at baseline, and it\u0026rsquo;s possible that participants\u0026rsquo; drinking habits may have changed during the follow-up period. Thirdly, although we adjusted for multi-dimensional confounders, residual confounding cannot be completely ruled out due to the observational nature of the study. Fourthly, the frequency of the rs671 polymorphism is low in the European population we studied. Significant results may be found for rs671 in populations with a higher frequency of the rs671 polymorphism, such as the Asian population.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, overall and beverage-specific alcohol consumption exhibit a J-shaped association with all-cause mortality, although some variations exist in the dose-response curves for disease-specific mortality. Moreover, the C allele of rs1229984 in ADH1B is associated with increased risk of mortality. Notably, a multiplicative interaction exists between alcohol consumption and rs1229984 for mortality, highlighting a higher risk of excessive alcohol use in individuals harboring the variant associated with low ADH1B activity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors extend their gratitude to all participants of the UK Biobank.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eDrs Changhai Ding and Yan Zhang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.\u003c/p\u003e\n\u003cp\u003eConcept and design: Changhai Ding, Yan Zhang.\u003c/p\u003e\n\u003cp\u003eAcquisition, analysis, or interpretation of data: Guangfeng Ruan, Zhaohua Zhu, Han Cen, Yuanyuan Wang, Muhui Zeng, Xizeng Zong, Jie Wang, Xingzhong Jin, Simin Wen, Siqi Xu.\u003c/p\u003e\n\u003cp\u003eDrafting of the manuscript: Guangfeng Ruan, Zhaohua Zhu, Han Cen, Yuanyuan Wang.\u003c/p\u003e\n\u003cp\u003eObtained funding: Guangfeng Ruan, Zhaohua Zhu, Yuanyuan Wang, Changhai Ding, Yan Zhang.\u003c/p\u003e\n\u003cp\u003eAdministrative, technical, or material support: Qian Yang, Yujie Zhang.\u003c/p\u003e\n\u003cp\u003eSupervision: Yan Zhang, Changhai Ding.\u003c/p\u003e\n\u003cp\u003eAll authors have read, revised and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work has been fully supported by the Guangdong Basic and Applied Basic Research Foundation (2023A1515011518), the National Natural Science Foundation of China (82373653 \u0026amp; 82472478), the Science and Technology Program of Guangzhou (2025A04J3955), the President Foundation of Nanfang Hospital, Southern Medical University (2021C006), and the Zhujiang Hospital Talent Recruitment Funds and Clinical Research Startup Program of Southern Medical University (no. LC2019ZD015).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eData availability statement\u003c/h2\u003e\n\u003cp\u003ePublicly available data from the UK Biobank study was analyzed in this study. The datasets are available to researchers through an open application via https://www.ukbiobank.ac.uk/use-our-data/apply-for-access/.\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe studies were carried out in accordance with the Helsinki Declaration of 1975 as revised in 1983.The UK Biobank data were approved by the North West Multi-centre Research Ethics Committee (MREC) (REC reference: 16/NW/0274). Additionally, our institution, Guangzhou First People\u0026apos;s Hospital, has granted an ethical approval exemption (K-2025-028-01).\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll participants provided written informed consent.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003ch2\u003ePatient and public involvement statement\u003c/h2\u003e\n\u003cp\u003ePatients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSinn DH, Kang D, Guallar E, et al. Alcohol Intake and Mortality in Patients With Chronic Viral Hepatitis: A Nationwide Cohort Study. Am J Gastroenterol. 2021;116(2):329\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXi B, Veeranki SP, Zhao M, Ma C, Yan Y, Mi J. Relationship of Alcohol Consumption to All-Cause, Cardiovascular, and Cancer-Related Mortality in U.S. Adults. J Am Coll Cardiol. 2017;70(8):913\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArranz S, Chiva-Blanch G, Valderas-Mart\u0026iacute;nez P, Medina-Rem\u0026oacute;n A, Lamuela-Ravent\u0026oacute;s RM, Estruch R. Wine, beer, alcohol and polyphenols on cardiovascular disease and cancer. Nutrients. 2012;4(7):759\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuo C, Yang Y, Yuan Z, et al. Alcohol Intake Interacts with Functional Genetic Polymorphisms of Aldehyde Dehydrogenase (ALDH2) and Alcohol Dehydrogenase (ADH) to Increase Esophageal Squamous Cell Cancer Risk. J Thorac oncology: official publication Int Association Study Lung Cancer. 2019;14(4):712\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao N, Chen J, Qi B, et al. Effects of Gene Polymorphisms, Metabolic Activity, and Content of Alcohol Dehydrogenase and Acetaldehyde Dehydrogenases on Prognosis of Hepatocellular Carcinoma Patients. Turkish J gastroenterology: official J Turkish Soc Gastroenterol. 2022;33(7):606\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChang TG, Yen TT, Wei CY, Hsiao TH, Chen IC. Impacts of ADH1B rs1229984 and ALDH2 rs671 polymorphisms on risks of alcohol-related disorder and cancer. Cancer Med. 2023;12(1):747\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEdenberg HJ. The genetics of alcohol metabolism: role of alcohol dehydrogenase and aldehyde dehydrogenase variants. Alcohol Res health: J Natl Inst Alcohol Abuse Alcoholism. 2007;30(1):5\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSakaue S, Akiyama M, Hirata M, et al. Functional variants in ADH1B and ALDH2 are non-additively associated with all-cause mortality in Japanese population. Eur J Hum genetics: EJHG. 2020;28(3):378\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrtol\u0026aacute; R, Garc\u0026iacute;a-Esquinas E, L\u0026oacute;pez-Garc\u0026iacute;a E, Le\u0026oacute;n-Mu\u0026ntilde;oz LM, Banegas JR, Rodr\u0026iacute;guez-Artalejo F. Alcohol consumption and all-cause mortality in older adults in Spain: an analysis accounting for the main methodological issues. Addiction (Abingdon England). 2019;114(1):59\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTopiwala A, Ebmeier KP, Maullin-Sapey T, Nichols TE. No safe level of alcohol consumption for brain health: observational cohort study of 25,378 UK Biobank participants. 2021.05.10.21256931.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDing C, O'Neill D, Bell S, Stamatakis E, Britton A. Association of alcohol consumption with morbidity and mortality in patients with cardiovascular disease: original data and meta-analysis of 48,423 men and women. BMC Med. 2021;19(1):167.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBycroft C, Freeman C, Petkova D, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDi Castelnuovo A, Bonaccio M, Costanzo S, et al. Drinking alcohol in moderation is associated with lower rate of all-cause mortality in individuals with higher rather than lower educational level: findings from the MORGAM project. Eur J Epidemiol. 2023;38(8):869\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKunzmann AT, Coleman HG, Huang WY, Berndt SI. The association of lifetime alcohol use with mortality and cancer risk in older adults: A cohort study. PLoS Med. 2018;15(6):e1002585.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTian Y, Liu J, Zhao Y, et al. Alcohol consumption and all-cause and cause-specific mortality among US adults: prospective cohort study. BMC Med. 2023;21(1):208.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsai MK, Gao W, Wen CP. The relationship between alcohol consumption and health: J-shaped or less is more? BMC Med. 2023;21(1):228.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChang CC, Zhao Y, Lee CW, Ganguli M. Smoking, death, and Alzheimer disease: a case of competing risks. Alzheimer Dis Assoc Disord. 2012;26(4):300\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang X, Liu Y, Li S, et al. Alcohol consumption and risk of cardiovascular disease, cancer and mortality: a prospective cohort study. Nutr J. 2021;20(1):13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlmeida OP, McCaul K, Hankey GJ, Yeap BB, Golledge J, Flicker L. Excessive alcohol consumption increases mortality in later life: a genetic analysis of the health in men cohort study. Addict Biol. 2017;22(2):570\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAkiyama M, Okada Y, Kanai M, et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat Genet. 2017;49(10):1458\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWarren HR, Evangelou E, Cabrera CP, et al. Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat Genet. 2017;49(3):403\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alcohol consumption, Genetic variants, Mortality, Interaction","lastPublishedDoi":"10.21203/rs.3.rs-7648401/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7648401/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIn studies regarding the association between alcohol consumption and mortality, controversy exists regarding the effects of light to moderate alcohol intake, and no study considered the role of alcohol metabolism related genetic variants in this relationship. Similarly, study investigating impact of alcohol consumption on the relationship between these genetic variations and mortality is also lacking. We therefore investigated the associations of alcohol consumption and alcohol metabolism related genetic variants with all-cause and disease-specific mortality, as well as the multiplicative interaction of alcohol consumption and the genetic variants\u003c/p\u003e\n\u003cp\u003eon mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eThis prospective cohort study utilized data from the UK Biobank. Restricted cubic splines were used to evaluate the shapes of the associations between alcohol consumption and all-cause and disease-specific mortality. Cox proportional hazards models were used to estimate hazard ratios for associations between alcohol intake and mortality, both before and after stratifying by the genetic variants. Similarly, associations between the genetic variants and mortality were also examined before and after stratifying by alcohol intake.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eAlcohol consumption had a J-shaped link with all-cause and most disease-specific mortality, except neurological. Similarly, beverage-specific intake showed a J-shaped relationship with all-cause mortality. The rs1229984 variant in ADH1B modifies the associations between alcohol consumption and mortality, resulting in elevated risks of all-cause and disease-specific mortality for individuals without the T allele when compared to carriers. Carriers of the rs1229984 C allele exhibited an increased risk of overall mortality. In stratified analyses, the hazard ratios of the rs1229984 C allele progressively rose from never drinkers to light drinkers, moderate drinkers, and ultimately to heavy drinkers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eThis study underscores the necessity of curbing excessive alcohol consumption to reduce mortality, particularly among individuals lacking the T allele of rs1229984.\u003c/p\u003e","manuscriptTitle":"Interaction of alcohol consumption and genetic variants in alcohol metabolism on all-cause and disease-specific mortality: a cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-03 16:53:36","doi":"10.21203/rs.3.rs-7648401/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"86345e32-b43b-43e6-ad42-bb148b8c5aa4","owner":[],"postedDate":"November 3rd, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-19T19:46:51+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T19:54:42+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-03 16:53:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7648401","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7648401","identity":"rs-7648401","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}