Moderation
A burden of proof study on alcohol consumption and ischemic heart disease
Authors
Carr S; Bryazka D; McLaughlin SA; Zheng P; Bahadursingh S; Aravkin AY; Hay SI; Lawlor HR; Mullany EC; Murray CJL; Nicholson SI; Rehm J; Roth GA; Sorensen RJD: Lewington S; Gakidou E
Citation
Nature Communications (2024) 15:4082. doi.org/10.1038/s41467-024-47632-7
Author’s Abstract
Objective Cohort and case-control data have suggested an association between low to moderate alcohol consumption and decreased risk of ischemic heart disease (IHD) yet results from Mendelian randomization (MR) studies designed to reduce bias have shown either no or a harmful association.
Methods Here we conducted an updated systematic review and re-evaluated existing cohort, case-control, and MR data using the burden of proof meta-analytical framework.
Results Cohort and case-control data show low to moderate alcohol consumption is associated with decreased IHD risk – specifically, intake is inversely related to IHD and myocardial infarction morbidity in both sexes and IHD mortality in males – while pooled MR data show no association, confirming that self-reported versus genetically predicted alcohol use data yield conflicting findings about the alcohol-IHD relationship.
Conclusions Our results highlight the need to advance MR methodologies and emulate randomized trials using large observational databases to obtain more definitive answers to this critical public health question.
Forum Summary
Another systematic review and re-evaluation of existing data using a relatively recent burden of proof meta-analytical framework (Zheng et al. 2022). The review suggests that traditional types of studies strongly support a j-shaped relationship between alcohol consumption and risk of ischaemic heart disease, but that Mendelian Randomization studies assessing genetic variation do not necessarily. Genes have some effects on risk but the type of beverage consumed, the rate of its consumption, the regularity of such consumption, whether with food, and whether there is binge drinking, are the major factors in determining the health effects of drinking. These are generally more determined by lifestyle or cultural habits and less influenced by genes.
Forum Comments
Background
Carr et al. (2024) re-evaluate the association between alcohol consumption and ischaemic heart disease (IHD). The authors were interested in this specific association since alcohol consumption increases the risk of morbidity and mortality on the one hand and decreases the risk of IHD on the other hand. Substantial interest exists in the alcohol-IHD relationship since the prevalence of alcohol consumption is high as is the prevalence of IHD.
The alcohol-IHD relationship is a long-lasting scientific discussion based on extensive epidemiological analyses, nutrition intervention studies, reviews, systematic reviews and meta-analyses. The new aspect of the current study is the use of the so-called burden of proof meta-analytical framework. Using this methodology, the authors conducted an updated systematic review and re-evaluated existing cohort, case-control, and Mendelian Randomization (MR) data. The burden of proof approach is a six-step framework consisting of gathering relevant information, evaluating study quality and correcting for potential confounders, ultimately calculating a conservative effect estimate. The key statistical tool consists of a flexible meta-regression tool that does not impose a log-linear relationship between the risk and outcome, but instead uses a spline ensemble to model non-linear relationships.
The authors summarize their findings as follows: results suggested an inverse association between alcohol and IHD when all conventional observational studies were pooled as well as in evaluating cohort studies only. When only case-control studies were pooled, also alcohol consumption was associated with a decrease in IHD risk up to high levels of consumption. Their analysis of the available MR studies showed no association between genetically predicted alcohol consumption and IHD.
The authors conclude there is a need to advance MR methodologies and emulate randomized trials using large observational databases to obtain more definitive answers to this critical public health question.
Critique
This study is interesting in that it uses a more advanced meta-analytical technique involving modelling showing that a J-shaped association exists between alcohol consumption and IHD with a nadir of approximately 23 g alcohol/day with a relative risk of 0.69. Myocardial infarction (MI) risk reduction was maximal at 15 g alcohol/day with a relative risk of 0.66. Even at the 85th percentile exposure level observed in the studies (45 g alcohol/day for IHD and 50 g alcohol/day for MI) a relative risk of 0.72 and 0.73 was calculated for IHD and MI, respectively.
Various criteria are used to adjust for common sources of bias in this methodology. One of these is exposure assessment, which was quantified by whether alcohol consumption was recorded once or more than once in conventional observational studies, or with only one or multiple SNPs (genetic variants) in MR studies. Although this improved meta-analytical methodology considers alcohol assessment, it still does not consider nor adjust for important factors like drinking frequency and underreporting as mentioned by the authors. A limited number of studies have investigated the effect of drinking pattern, mainly because alcohol exposure assessment is complex and usually not extensively captured in questionnaires. Those studies that did analyse the effect of drinking pattern have suggested that it is an important factor (Joan et al. 2003, Ruidavets et al., 2010, Ellison, 2005, Rimm and Moats 2007, Roerecke and Rehm 2014, Sarich et al. 2020, Jani et al. 2021 Ding et al. 2023. Studying the effects of drinking frequency and drinking pattern seems essential in further diversifying the alcohol-IHD relationship.
The study by Carr et al. (2024) also shows that MR studies cannot find a similar association as found in classical high-quality epidemiology. This leads the authors to conclude that MR studies need to improve. In other words, MR studies are not (yet) able to correctly describe a complex association as the alcohol-IHD one. The authors indicate that MR studies do not (sufficiently) allow for non-linear associations such as those for alcohol consumption and IHD. This is probably caused by insufficient genetic variation testing, which does not allow for the study of dose-dependency and drinking pattern. Also, other factors like the motivation to drink or other characteristics of the alcohol consumer such as impulsivity (Villafuerte et al., 2012), sensation seeking (Weiland et al., 2013), neuronal disinhibition and an impaired ability to easily learn from mistakes (Mayfield et al., 2008) are not included in MR studies. Yet other relevant factors, like drinking with meals and gender are not captured in MR studies. So, with limitations both in terms of the number of genes involved in drinking behaviour, as well as the genetic variation in these genes, MR studies may only focus on a minority of relevant factors determining drinking behaviour.
This paper essentially puts forward the notion that MR studies are not suitable to study the alcohol-IHD association nor the associations between alcohol consumption and any other disease outcome.
The authors are not clear, however, on the role of intervention studies. They argue that studies, like the cancelled long-term MACH15 study, would have made a difference. Conversely, they argue that the implementation of a long-term trial would have been fraught with potential issues, such as ethical questions related to alcohol carcinogenicity. This is surprising since Medical Ethics Committees always weigh the scientific benefits against the potential risks for volunteers entering the studies. Medical Ethics Committees also assume the principle of acceptable risk rather than a zero-risk tolerance, which seems to be the current standard for alcohol consumption. Moderate alcohol consumption as proposed in MACH15 study, is associated with a very small increase in cancer risk, if any (Hendriks & Calame, 2018, Cao et al., 2015).
The authors appear to suggest in their last sentence of the abstract that they would be in favour of the idea of a long-term clinical trial as the MACH15 study, since such a study would provide further causal insight in the alcohol-IHD relationship. This is needed since epidemiology is convincing to most, but not to all. A potential alternative, the MR technology is, however, insufficiently developed and may even be unsuitable for the very complex multifactorial alcohol-IHD relationship.
Short-term trials were briefly mentioned in this study, but not included in the overall analysis. This may be a missed opportunity since quite a lot of mechanistic work has been performed by these short-term nutrition interventions (Rimm et al., 1999, Brien et al., 2011). Biomarker changes observed in nutrition interventions have led to estimated contributions in epidemiological associations. This type of analysis has led to the notion that most of the benefit from the alcohol-IHD association could be explained by observable biomarker changes (Mukamal et al., 2005). The main contributing changes in the alcohol-IHD protective relationship were HDL-cholesterol increase, fibrinogen decrease and HbA1c decrease, indicating improvements in lipid metabolism, haemostasis and glucose homeostasis. This means that not only the conventional observational studies are consistent (Ronksley et al., 2011), but also that a mechanism has been elucidated which may fully explain the association observed.
Large and long-lasting observational studies may be used to study the changes in disease incidences associated with changes in drinking behaviour. For example, studies looking into drinking behaviour changes and the incidence of diabetes type 2 (Joosten et al., 2011) have shown that increases in alcohol consumption over time were associated with a lower risk of type 2 diabetes among initially rare and light drinkers. This lower risk was evident within four years following increased alcohol consumption.
Both approaches, integrating short-term nutrition intervention biomarker changes with epidemiological analysis and changes in alcohol consumption associated with disease outcomes over time, could add to the existing extensive epidemiological evidence on the alcohol-IHD association.
Specific Comments from Forum Members
Forum Member Skovenborg also suggests that there is a lack of studies where alcohol exposure includes drinking patterns and drinking while fasting/having a meal. He then suggests that the studies used as reference for that statement by Carr et al. (23024) that “even low levels of consumption increase the risk of some cancers”, have serious flaws as follows:
“The “low levels”, for example, 10 grams of alcohol per day, is typically a fictional level constructed by dividing the consumption of alcohol by seven. That means we do not know whether the individual consumes one drink daily or seven drinks during the weekend. It is plausible that the alcohol-cancer association is very different whether you are a regular drinker of one glass of wine with your meal or a weekend binge drinker. Strangely, Carr et al. (2024) accept the association of cancer and alcohol intake without question while they find the cohort and case-control studies of alcohol and IHD subject to a number of various types of bias.
While the authors’ analysis of Mendelian Randomisation studies of alcohol and the risk of IHD found no effect of alcohol consumption, they do not mention most Mendelian Randomisation studies of alcohol and breast cancer found no association between alcohol consumption and the risk of breast cancer. These interesting results tend to be “lost” in the reviews of alcohol and breast cancer. We should suggest that Carr et al. (2024) ought to use the burden of proof study technique to analyse the association between low levels of alcohol consumption and the risk of some cancers.”
In addition, Forum Member Harding comments that he “shares the reservations expressed about the statement, ‘with even low levels of consumption increasing the risk for some cancers’. In addition to the points already made, I note that both the two papers cited (Bagnardi et al. 2015, and Wood et al. 2018) pass off epidemiological association as causality, which is uncritically accepted by Carr et al. (2024). Furthermore, the paper appears to further undermine the notion that the Mendelian Randomisation approach is the ‘gold standard’, as I have heard it described. It has already been pointed out that it is subject to the same limitations as instrumental variable analysis, and a few more as well (Mukamal et al. 2020).”
Concluding comments
Forum Member Ellison noted that he “rarely tends to review articles on the effects of alcohol estimated by MR, as most MR approaches thus far are inadequate ways of studying the health effects of alcohol (Ellison, et al, 2021). Even if such an approach gave a good estimate of the number of drinks someone consumed, it must be realized that the amount of alcohol consumed per week (or other period of time) is not as important as the pattern of consumption.
Genes obviously have some effects, but the type of beverage consumed, the rate of consumption, the regularity of such consumption, whether with food, and whether there is binge drinking, are all major factors in determining the health effects of drinking. These are generally more determined by lifestyle or cultural habits learned while one is growing up and less influenced by genes.
There is an immense amount of data from large cohort studies indicating that the regular consumption of moderate amounts of wine with meals is associated especially with a lower risk of cardiovascular disease and total mortality (Ellison et al. 2021).”
References
Bagnardi, V. et al. (2015) Alcohol consumption and site-specific cancer risk: a comprehensive dose–response meta-analysis. Br. J. Cancer, 112, 580–593.
Brien, S. E., Ronksley, P. E., Turner, B. J., Mukamal, K. J., & Ghali, W. A. (2011). Effect of alcohol consumption on biological markers associated with risk of coronary heart disease: systematic review and meta-analysis of interventional studies. BMJ, 342, d636. doi.org/10.1136/bmj.d636
Cao, Y., Willett, W. C., Rimm, E. B., Stampfer, M. J., & Giovannucci, E. L. (2015). Light to moderate intake of alcohol, drinking patterns, and risk of cancer: results from two prospective US cohort studies. BMJ, 351, h4238. doi.org/10.1136/bmj.h4238
Ding, C., Fat, L.N., Broitton, A., Im P.K., Lin, K., Topiwala, A., Li, L., Chen, Z., Millwood, I.Y., Bell, S., Mehta, G. (2023) Binge pattern alcohol consumption and genetic risk as determinants of alcohol-related liver disease. Nature Comm, 14, 8041.
Ellison, R. C. (2005). Importance of pattern of alcohol consumption. Circulation, 112 (25), 3818–3819. doi.org/10.1161/CIRCULATIONAHA.105.590331
Ellison, R.C., Gronbaek, M., Skovenborg, E. (2021). Using Mendelian randomization to evaluate the effects of alcohol consumption on the risk of coronary heart disease. Drugs Alcohol Today, 21-1, 84-95.
Hendriks, H. F. J., & Calame, W. (2018). The contribution of alcohol consumption to overall cancer incidence in the Western World: a meta-analysis. J Nutr Health Sci, 5(3), 311.
Jani, B.D., McQueenie, R., Nicholl, B.I. et al. (2021) Association between patterns of alcohol consumption (beverage type, frequency and consumption with food) and risk of adverse health outcomes: a prospective cohort study. BMC Med, 19, 8. doi.org/10.1186/s12916-020-01878-2
Dorn, J., Hovey, K., Muti, P., Freudenheim, J., Trevisan, M., Russell, M., Nochajski, T.H. (2003) Alcohol Drinking Patterns Differentially Affect Central Adiposity as Measured by Abdominal Height in Women and Men, J Nutr, 133(8), 2655-2662. doi.org/10.1093/jn/133.8.2655.
Joosten, M. M., Chiuve, S. E., Mukamal, K. J., Hu, F. B., Hendriks, H. F. J., & Rimm, E. B. (2011). Changes in alcohol consumption and subsequent risk of type 2 diabetes in men. Diabetes, 60(1), 74–79. doi.org/10.2337/db10-1052
Mayfield, R. D., Harris, R. A., & Schuckit, M. A. (2008). Genetic factors influencing alcohol dependence. Br J Pharmacol, 154(2), 275–287. doi.org/10.1038/bjp.2008.88
Mukamal, K. J., Jensen, M. K., Grønbæk, M., Stampfer, M. J., Manson, J. E., Pischon, T., & Rimm, E. B. (2005). Drinking Frequency, Mediating Biomarkers, and Risk of Myocardial Infarction in Women and Men. Circulation, 112(10), 1406–1413. doi.org/10.1161/CIRCULATIONAHA.105.537704
Rimm, E.B., Moats, C. (2007) Alcohol and Coronary Heart Disease: Drinking Patterns and Mediators of Effect, Ann Epidemiol, 17(5), S3-S7.
Rimm, E. B., Williams, P., Fosher, K., Criqui, M., & Stampfer, M. J. (1999). Moderate alcohol intake and lower risk of coronary heart disease: meta-analysis of effects on lipids and haemostatic factors. BMJ (Clin Res Ed.), 319(7224), 1523–1528. doi.org/10.1136/bmj.319.7224.1523
Roerecke, M., & Rehm, J. (2014) Alcohol consumption, drinking patterns, and ischemic heart disease: a narrative review of meta-analyses and a systematic review and meta-analysis of the impact of heavy drinking occasions on risk for moderate drinkers. BMC Med, 12, 182. doi.org/10.1186/s12916-014-0182-6
Ronksley, P. E., Brien, S. E., Turner, B. J., Mukamal, K. J., & Ghali, W. A. (2011). Association of alcohol consumption with selected cardiovascular disease outcomes: a systematic review and meta-analysis. BMJ, 342, d671. doi.org/10.1136/bmj.d671
Ruidavets, J.-B., Ducimetière, P., Evans, A., Montaye, M., Haas, B., Bingham, A., Yarnell, J., Amouyel, P., Arveiler, D., Kee, F., Bongard, V., & Ferrières, J. (2010). Patterns of alcohol consumption and ischaemic heart disease in culturally divergent countries: the Prospective Epidemiological Study of Myocardial Infarction (PRIME). BMJ (Clin ResEd.), 341, c6077. doi.org/10.1136/bmj.c6077
Villafuerte, S., Heitzeg, M. M., Foley, S., Yau, W. Y., Majczenko, K., Zubieta, J. K., Zucker, R. A., & Burmeister, M. (2012). Impulsiveness and insula activation during reward anticipation are associated with genetic variants in GABRA2 in a family sample enriched for alcoholism. Mol Psychiatry, 17(5), 511–519. doi.org/10.1038/mp.2011.33
Weiland, B. J., Welsh, R. C., Yau, W. Y., Zucker, R. A., Zubieta, J. K., & Heitzeg, M. M. (2013). Accumbens functional connectivity during reward mediates sensation-seeking and alcohol use in high-risk youth. Drug Alcohol Depend, 128(1–2), 130–139. doi.org/10.1016/j.drugalcdep.2012.08.019
Wood, A. M. et al. (2018) Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies. Lancet, 391, 1513–1523.
Zheng, P., Afshin, A., Biryukov, S. et al. (2022) The Burden of Proof studies: assessing the evidence of risk. Nat Med, 28, 2038–2044. doi.org/10.1038/s41591-022-01973-2
Comments on this critique by the International Scientific Forum on Alcohol Research were provided by the following members:
Henk Hendriks, PhD, Netherlands
Creina Stockley, PhD, MBA, Independent consultant and Adjunct Senior Lecturer in the School of Agriculture, Food and Wine at the University of Adelaide, Australia
Erk Skovenborg, MD, specialized in family medicine, member of the Scandinavian Medical Alcohol Board, Aarhus, Denmark
Giovanni Gaetano, MD, PhD, Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo NEUROMED, Pozzilli, Italy
Fulvio Ursini, MD, Dept. of Biological Chemistry, University of Padova, Padova, Italy
Fulvio Mattivi, MSc, Scientific Advisor, Research and Innovation Centre, Fondazione Edmund Mach, in San Michele all’Adige, Italy
Richard Harding, PhD, Formerly Head of Consumer Choice, Food Standards and Special Projects Division, Food Standards Agency, UK
R Curtis Ellison, MD, Section of Preventive Medicine/Epidemiology, Boston University School of Medicine, Boston, MA, USA