Critique #297 – Two studies examine the associations of alcohol consumption with incident dementia
- Chen Y, Yin X, Wang X, Zheng X, Yang X, Zhou J, Shi M, Zhang Y. Associations of alcohol drinking with incident dementia: a prospective study from the UK Biobank. Eur J Epidemiol. 2025 Sep 27. doi: 10.1007/s10654-025-01304-y. Epub ahead of print. PMID: 41014391.
Abstract
Objectives: The relationship between alcohol drinking and incident dementia remained uncertain. This study used UK Biobank cohort data to investigate the association between alcohol drinking and dementia risk, and potential effect modifications by cardiovascular disease (CVD) risk, APOE4 gene, and sex.
Method: We excluded infrequent drinkers and participants with baseline dementia or dementia within two years of follow-up. Drinking status was defined as non-drinking, low-moderate and heavy drinking (by weekly alcohol units). Drinking behaviours included drinking with meals and drinking type. Primary outcome was all-cause dementia. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated by multivariable Cox regression models. Subgroup analyses stratified by CVD risk, APOE4 gene, and sex were conducted.
Results: Among 296,715 participants (mean age 56.54 years), 4,242 developed dementia over a median follow-up of 13.7 years. Compared to non-drinking, low-to-moderate drinking was associated with a reduced dementia risk (HR, 0.65; 95% CI, 0.59-0.73), while heavy drinking showed no significant association (HR, 0.88; 95% CI, 0.75-1.02). All drinking behaviours lowered dementia risk. Low-to-moderate drinking reduced dementia risk across subgroups: high/low CVD risk (HR 0.66, 95% CI 0.59-0.74/0.43, 0.30-0.61), APOE4 carriers/non-carriers (HR 0.71, 0.61-0.83/0.61, 0.52-0.71), females/males (HR 0.67, 0.58-0.77/0.63, 0.53-0.76). Compared with non-drinking, low-to-moderate drinking is associated with lower incident dementia risk, regardless of CVD risk, APOE4 gene, and sex. The protective effect of alcohol drinking was consistent among various drinking behaviours.
Conclusions: Thus, this study confirmed the protective effect of low-moderate drinking in the population and provided insights for improving alcohol-related public health guidelines for dementia prevention.
2. Topiwala A, Levey DF, Zhou H, Deak JD, Adhikari K, Ebmeier KP, Bell S, Burgess S, Nichols TE, Gaziano M, Stein M, Gelernter J. Alcohol use and risk of dementia in diverse populations: evidence from cohort, case-control and Mendelian randomisation approaches. BMJ Evid Based Med. 2025 Sep 23:bmjebm-2025-113913. doi: 10.1136/bmjebm-2025-113913. Epub ahead of print. PMID: 40987604.
Abstract
Objectives: To investigate the relationship between alcohol consumption and dementia.
Design: Prospective cohort and case-control analyses combined with linear and non-linear Mendelian randomisation.
Setting: Two large-scale population-based cohorts: the US Million Veteran Programme and the UK Biobank. Genetic analyses used summary statistics from genome-wide association studies (GWAS).
Participants: 559 559 adults aged 56-72 years at baseline were included in observational analyses (mean follow-up: 4 years in the US cohort; 12 years in the UK cohort). Genetic analyses used summary data from multiple large GWAS consortia (2.4 million participants).
Main outcome measures: Incident all-cause dementia, determined through health record linkage, and genetic proxies.
Results: During follow-up, 14 540 participants developed dementia and 48 034 died. Observational phenotype-only analyses revealed U-shaped associations between alcohol and dementia risk: higher risk was observed among non-drinkers, heavy drinkers (>40 drinks per week; HR 1.41, 95% CI 1.15 to 1.74), and those with alcohol use disorder (AUD) (HR 1.51, 95% CI 1.42 to 1.60) compared with light drinkers. In contrast, Mendelian randomisation genetic analysis identified a monotonic increase in dementia risk with greater alcohol consumption. A 1 SD increase in log-transformed drinks per week was associated with a 15% dementia increase (inverse-variance weighted (IVW) OR 1.15, 95% CI 1.03 to 1.27). A twofold increase in AUD prevalence was associated with a 16% increase in dementia risk (IVW OR 1.16, 95% CI 1.03 to 1.30). Alcohol intake increased dementia, but individuals who developed dementia also experienced a decline in alcohol intake over time, suggesting reverse causation-where early cognitive decline leads to reduced alcohol consumption-underlies the supposed protective alcohol effects in observational studies.
Conclusions: These findings provide evidence for a relationship between all types of alcohol use and increased dementia risk. While correlational observational data suggested a protective effect of light drinking, this could be in part attributable to reduced drinking seen in early dementia; genetic analyses did not support any protective effect, suggesting that any level of alcohol consumption may contribute to dementia risk. Public health strategies that reduce the prevalence of alcohol use disorder could potentially lower the incidence of dementia by up to 16%.
ISFAR summary
The studies by Chen et al. (2025) and Topiwala et al. (2025) provide complementary insights into the long-standing debate about the link between alcohol consumption and dementia risk. The Chen et al. study exemplifies a traditional longitudinal cohort analysis, showing the familiar U- or J-shaped relationship between alcohol consumption and dementia incidence in the UK Biobank. Building on this, Topiwala et al. expanded the analysis by including data from both the UK Biobank and the U.S. Million Veteran Program, and by applying Mendelian randomisation (MR) using genome-wide association study (GWAS) summary statistics as proxies for alcohol consumption.
Both studies indicate that light-to-moderate drinkers have the lowest risk according to conventional observational methods. However, when Topiwala et al. applied MR, the relationship was no longer J-shaped. Instead, dementia risk increased linearly with genetically predicted alcohol consumption. The use of genetic instruments aims to better reflect lifelong exposure. Nonetheless, genetic proxies only capture part of the complex social and behavioural factors affecting alcohol consumption, and their explanatory power remains limited. For example, Topiwala et al. used 641 variants to predict drinks per week and 66 for alcohol use disorder, but the correlation between these genetic predictors and reported intake was not given, raising doubts about the validity of the instruments.
Topiwala et al. suggest that traditional epidemiological associations based on self-reported exposures may need re-evaluation in light of genetic evidence. While this position underscores the value of MR as a complementary approach, it is important not to overstate its scope: genetic proxies do not fully account for environmental, social, or behavioural influences on alcohol consumption.
ISFAR critique
Background
Cognitive function encompasses the mental processes by which knowledge is acquired and applied, including perception, reasoning, problem-solving, creativity, and intuition. Dementia is a clinical syndrome marked by progressive cognitive decline severe enough to impair daily life and independence. It is an umbrella term for conditions that cause deterioration of normal brain functions rather than a single disease entity. The most common forms include Alzheimer’s disease (AD), vascular dementia (VD), dementia with Lewy bodies, and frontotemporal dementia (FTD) (Steinman et al., 2021).
While the underlying causes vary, many share overlapping pathways. Ageing contributes through vascular stiffening, microvascular damage, reduced repair capacity, and mitochondrial decline. Genetic factors, notably the APOE ε4 allele, increase Alzheimer’s risk via effects on lipid metabolism, amyloid clearance, and vascular health (Tarawneh, 2023). Familial AD arises from APP, PSEN1, or PSEN2 mutations, while FTD involves genes such as MAPT, progranulin, and C9orf72. Vascular and metabolic disorders—including hypertension, diabetes, obesity, and hyperlipidaemia—further elevate dementia risk (Attems & Jellinger, 2014).
Additional mechanisms include chronic neuroinflammation, oxidative and mitochondrial stress, and protein aggregation leading to neuronal death and network disruption. Mixed pathologies, where vascular and amyloid/tau changes coexist, are common and may act synergistically, for example, through cerebral amyloid angiopathy. Globally, dementia prevalence is rising rapidly with population ageing, with around 10 million new cases each year.
Given its growing burden, there is intense interest in modifiable risk factors. Lifestyle elements such as diet and alcohol consumption are among the most studied. Earlier research has often shown a J-shaped association between alcohol intake and dementia risk, with low-to-moderate consumption linked to lower risk and heavy drinking or abstinence linked to higher risk (Rehm et al., 2019).
Critique
Two studies by Chen et al. 2025 and Topiwala et al. 2025 recently examined the link between alcohol consumption and dementia risk.
1. Chen et al. (2025)
Chen et al. (2025) recently reported that low-to-moderate alcohol consumption was associated with a decreased risk of dementia in the UK Biobank. Their large sample of 296,715 individuals, combined with an extended follow-up of approximately 13.7 years, provides valuable observational data, including subgroup analyses and considerations of drinking behaviours. Notably, unlike many earlier observational studies, this study excluded former drinkers and infrequent drinkers from the analysis cohort. This minimises the common “sick quitter” bias, which has previously been suggested to inflate the apparent benefits of moderate drinking. The study also benefited from extensive covariate adjustments and sensitivity analyses using multiple imputation and complete-case samples. Alcohol consumption was categorised into non-drinking, low-moderate, and heavy drinking (with sex-specific thresholds). Behaviours such as drinking with meals and types of drinks were also assessed. Using multivariable Cox regression, they found that low-moderate drinking (compared to non-drinking) was associated with a significantly lower hazard of dementia (HR ~0.65, 95% CI 0.59–0.73), while heavy drinking showed a non-significant trend (HR ~0.88, 95% CI 0.75–1.02). The ‘protective’ link of low-moderate drinking seemed consistent across subgroups such as cardiovascular disease risk, APOE4 status, and gender. The authors interpret this as support for a protective effect of low- to moderate drinking against dementia. However, caution is advised when interpreting the findings, as alcohol consumption was only assessed at baseline without considering lifetime drinking patterns or reductions before dementia onset, which raises the possibility of reverse causation.
The greatest strength of Chen et al. (2025) lies in its large, well-characterised, prospective cohort design using the UK Biobank, which combines long-term follow-up (median 13.7 years) with detailed individual-level data on alcohol consumption and health covariates. Specifically, with 297,000 participants and over 4,000 incident dementia cases, Chen et al. (2025) have strong statistical power to detect associations and analyse subgroups. The UK Biobank provides extensive information on demographics, cardiovascular risk factors, APOE4 genotype, socioeconomic status, physical activity, diet, and mental health, allowing for comprehensive adjustment of potential confounders. Missing data were addressed using multiple imputation and confirmed through complete-case sensitivity analyses. While these features enhance internal validity, a limitation of the UK Biobank is that participants are generally healthier, wealthier, and less ethnically diverse than the broader UK population, which may limit generalisability and bias exposure–outcome associations if relationships differ in underrepresented groups.
In addition to these methodological strengths, Chen et al. (2025) assessed detailed drinking behaviours—including beverage type, drinking with meals, and effect modification by sex, APOE4 status, and cardiovascular risk—providing important insights into heterogeneity across population subgroups. This behavioural detail enhances real-world relevance and clarifies how drinking patterns may relate to dementia outcomes. The exclusion of participants with pre-existing dementia and those diagnosed within the first two years further strengthened temporal inference, although reverse causation from prodromal disease cannot be fully excluded.
The primary weakness of Chen et al. (2025), however, lies in their dependence on a single baseline measure of alcohol consumption, which renders the study vulnerable to exposure misclassification and reverse causation over time. For example, since alcohol consumption was only assessed at baseline without accounting for lifetime drinking patterns or reductions before the onset of dementia, this raises the possibility of reverse causation. In fact, a single baseline measurement can lead to misclassification of exposure and fails to address some risks associated with reverse causation. Heavy drinkers also face elevated risks of premature death from other causes, such as liver disease, cancer, and CVD. Standard Cox models censor at death and assume non-informative censoring, potentially underestimating harm in heavy drinkers; no competing-risk analysis was conducted. Furthermore, drinking behaviour often changes significantly with age, health, or emerging cognitive decline. Individuals who later develop dementia may already have reduced their intake well before diagnosis, creating a misleading impression of a protective effect for moderate drinkers. Additionally, the study lacks data on cumulative or peak lifetime consumption, which is crucial for understanding long-term neurotoxicity or harm thresholds. Although the authors excluded dementia cases within the first two years, prodromal cognitive changes can begin a decade or more prior to clinical diagnosis. Consequently, reverse causation cannot be fully ruled out even after this exclusion. Without repeated exposure assessments, instrumental variable analyses (e.g., Mendelian randomisation), or sensitivity analyses for time-varying confounding, the study cannot definitively distinguish correlation from causation.
2. Topiwala et al. (2025)
In contrast to Chen et al. (2025), Topiwala et al. (2025) combined observational analyses with Mendelian randomisation (MR) using genome-wide association study (GWAS) data from over 2.4 million individuals across two major cohorts—the U.S. Million Veteran Program (MVP) and the UK Biobank—encompassing approximately 559,559 participants aged 56 to 72 years for the observational analyses. Dementia outcomes were identified through health record linkage and electronic health records (EHR) using ICD codes. The observational analyses revealed a J-shaped association, with both heavy drinkers and non-drinkers (particularly those with alcohol use disorder) showing higher dementia risk compared to light drinkers. However, the MR analyses indicated a monotonic increase in dementia risk with greater genetically predicted alcohol consumption, offering no evidence of a protective effect. Furthermore, trajectory data suggested that participants who later developed dementia often reduced their alcohol consumption in the years before diagnosis, supporting the likelihood of reverse causation and explaining the apparent benefits observed among moderate drinkers in observational data. Topiwala et al. (2025), therefore, concluded that there is no safe or protective threshold for alcohol consumption regarding dementia risk, directly challenging the longstanding “moderate drinking is protective” hypothesis.
The strengths of this approach are that combining observational and genetic (MR) evidence aids causal inference, offering a check on whether observed associations result from confounding or reverse causation. Furthermore, the large sample sizes in both the observational and existing Alzheimer’s disease genome-wide association study (GWAS) populations enhance the precision of their estimates. The use of multiple cohorts or diverse MVP and UK Biobank populations improves diversity and external validity, although MVP is predominantly male. Most importantly, they considered reverse causation, that is, observed declines in drinking before dementia diagnosis, addressing this potential bias. A non-linear MR and multiple alcohol phenotypes—such as drinks per week, problematic alcohol use, and AUD—provide additional robustness.
Topiwala et al. (2025) used GWAS summary statistics as proxies for alcohol consumption, assuming these may better reflect lifelong consumption than self-reported measures, which in most longitudinal studies are recorded only once at baseline and are prone to recall error and underreporting. However, genetic variation alone cannot fully capture a complex behaviour like alcohol consumption, which is influenced by social and lifestyle factors that change over time. Constructing such proxies is challenging—66 variants were used to predict alcohol use disorder and 641 for drinks per week—yet the authors did not report how well these genetic instruments correlated with self-reported consumption. Although not the focus of their study, presenting this comparison would have helped clarify the validity of the genetic proxies.
The main weakness of Topiwala et al. (2025), however, stems from the heterogeneity and limitations of their data sources, particularly their reliance on electronic health record (EHR)–based dementia diagnoses and self-reported alcohol consumption across different cohorts. This dependence may cause misclassification of exposures and outcomes, potentially biasing the MR analyses. For example, dementia cases were identified using health records (ICD codes) in both the UK Biobank and the MVP cohorts. These registries often under-detect milder or undiagnosed cases, and diagnostic coding practices can vary between healthcare systems. Such variation can result in non-differential misclassification, which weakens associations, or differential misclassification across exposure groups. Additionally, alcohol consumption was self-reported, and measurement methods differed between the cohorts. These differences can mask true dose–response relationships and make comparisons across cohorts difficult. While MR reduces confounding, it assumes that genetic variants influence dementia risk solely through alcohol consumption. However, pleiotropy—where genes affect multiple traits, such as smoking, education, or vascular risk—can bias causal estimates. The strongest genetic evidence is found among participants of European ancestry, with less reliable data for other groups. The MVP cohort mainly comprises males and older individuals, whereas the UK Biobank cohort tends to be healthier and more affluent than the general population. These differences limit the generalisability of the findings and may distort effect estimates if sex, age, or socioeconomic factors interact with alcohol’s effects. Additionally, the follow-up period was shorter in the MVP (approximately four years) compared to the UK Biobank (approximately 12 years), which could lead to an underestimation of dementia cases and increased short-term bias. The distinction between former drinkers and never drinkers may also be imperfect, although the study notes that non-/never drinkers had a similar risk to heavy drinkers in some analyses. The potential influence of “sick quitters” might still be present within the observational component.
Conclusions for the comparison and interpretation of Chen et al. (2025) and Topiwala et al. (2025)
Chen et al.’s (2025) greatest strength lies in its combination of large-scale, long-term prospective follow-up and detailed, behaviourally nuanced data from a well-characterised cohort, enabling precise and extensively adjusted estimates of the observational relationship between alcohol and dementia risk. Topiwala et al. (2025), however, are more robust in causal inference because of the MR component, a larger and more diverse sample, and the ability to test whether protective observational associations persist under genetic instruments. Since MR indicates a monotonic increase in risk, this more directly challenges the idea that light to moderate drinking is protective, as the triangulation of very large observational and genetic datasets lends their conclusions high credibility. Nevertheless, there remains the potential for exposure and outcome misclassification across heterogeneous cohorts, and the limitations of MR assumptions—although it provides greater causal insight—may still bias or weaken estimates of alcohol’s impact on dementia. Taken together, however, these studies highlight the divergence between observational and genetic evidence. Chen et al. (2025) provide high-quality observational evidence, strengthened by the exclusion of former drinkers; however, causal inference remains uncertain. In contrast, Topiwala et al. (2025) undermine the case for a protective effect through genetic triangulation. Public health interpretation should, therefore, remain cautious: while moderate drinking may appear protective in observational cohorts, there is insufficient evidence to recommend alcohol consumption for dementia prevention.
Specific comments
Forum member Ellison appreciated the authors’ extensive work in relating alcohol to dementia, using analyses of very large data sets. “In both papers, the observational data clearly demonstrate a J-shaped or U-shaped association between light-to-moderate drinking and dementia.
Despite recent progress in combining many factors in genetic analyses, I remain very uneasy about using MR to provide the only index of exposure in studies such as these (Ellison et al, 2021). MR relates genetic factors that influence alcohol consumption and its effects, but not the actual amounts consumed or the pattern of consumption.
MR fails to judge many cultural factors specific to the population being studied, such as the influence of peers, religious prohibitions and other societal factors, acceptance of alcohol within a specific population, education, and many socioeconomic factors. There are many such lifestyle factors that are more related to culture rather than to genetics, and these limit the usefulness of MR as the sole factor in determining the association between drinking and dementia.”
Forum member Harding states that “here are two epidemiological studies studying the effect of alcohol consumption on dementia. One study (Chen et al. 2025) shows, as do numerous earlier studies, that moderate alcohol consumption is associated with a reduced risk of all-cause dementia, Alzheimer’s disease, and vascular dementia. Indeed, Neafsey and Collins conducted a review in 2011 and concluded that ‘these studies overwhelmingly found that moderate drinking reduced or had no effect on the risk of dementia or cognitive impairment’. The other study (Topiwala et al. 2025) showed the same (although they used light to moderate drinkers as the reference group rather than abstainers). This protective association disappeared when they applied a MR approach.
Topiwala et al. (2025) concludes that because the results of MR genetic analysis did not show an association between alcohol consumption and protection against dementia, then argued that this demonstrates that no such association actually exists. I don’t accept this. Just because an epidemiological study (MR or otherwise) did not show an association does not mean that a causal association does not exist. It just didn’t find it, that all. For this reason, I conclude that the statement in the last paragraph of Topiwala et al. (2025) ‘…with no evidence supporting the previously suggested protective effect of moderate drinking’ cannot be justified, as their own study provided evidence. Both papers are based on the idea that it is epidemiology that can demonstrate whether alcohol consumption is protective for dementia. Just do enough of it and the truth will emerge. But in fact, epidemiology alone can never prove or disprove causation. In Chen et al. (2025), there is a nod in the direction of the actual effects of alcohol on dementia (references #40 and #41), but there is a lot more.
There are numerous animal studies indicating a protective effect. For example, moderate alcohol intake improves memory in rats (Kalev-Zylinska et al. 2007), and that resveratrol prevents the formation of beta-amyloid protein (Rushworth et al. 2013). Among human studies, alcohol consumption was associated with improved metal functioning in the Whitehall study, where 6000 civil servants were given tests of cognitive function and memory (Britton et al. 2004), consistent with a finding replicated in the Framingham Heart Study (Elias et al. 1999), and a study in the Netherlands (Kalminj et al. 2002). As far back as 1997, drinking up to 500ml of red wine/day was associated with a reduction of dementia by 80% and Alzheimer’s disease by 70% – huge effects (Orgogozo et al. 1997). There is even work on the impact of alcohol consumption on precursors of dementia revealed by MRI scans on those free of dementia symptoms, which showed a marked protective effect (den Heijer et al. 2004, Mukamal et al. 2001).
Finally, in the light of well-established effects of alcohol on insulin sensitivity and insulin resistance, and the similarities observed between Alzheimer’s disease and diabetes (sometimes called Type 3 diabetes), there is a resonance with more recent hypotheses on the consequences of insulin resistance on a whole range of chronic diseases. With a body of evidence this strong, it is hard to see a justification for writing either the Chen et al. or Topiwala et al. papers in the first place. The science has already moved on, a long time ago.
Forum member Skovenborg muses that all the published MR studies have found no association between alcohol consumption and risk of breast cancer, such that if MR studies are the golden truth, that is good news for wine-drinking women. “Some research purporting protective effects of moderate alcohol consumption” Topiwala et al. (2025) write quoting a 2003 nested case-control study of 373 cases with incident dementia and 373 controls. “Purporting” means to claim to be or do something, often in a way that may not be true or is not yet verified. It implies a declaration or appearance of intent or quality that might be false. Actually, since 1977, more than 189 case-control and cohort studies of alcohol intake and risk of dementia have been published with somewhat heterogeneous results. The overall finding is a significant association between moderate alcohol consumption and a reduced cognitive decline equivalent to being 3-4 years younger in the brain.
Topiwala et al. (2025) suggest reverse causation as one of the possible explanations. The concept of reverse causation refers to a process in which the consequence occurs before the cause. In a meta-analysis of 19 prospective observational cohort studies to examine whether physical inactivity is a risk factor for dementia separate analyses were performed that addressed bias due to reverse causation. These analyses found that physical inactivity was not associated with all-cause dementia or Alzheimer’s disease. However, an indication of excess dementia risk was observed in a subgroup of physically inactive individuals who developed cardiometabolic disease. An extended follow-up is needed to demonstrate a reverse causation bias. In the Whitehall II Cohort Study, the 23-year follow-up included eight assessments of alcohol consumption between 1985/88 and 2015/16. Participants with long-term abstinence had a 74 % increased risk of dementia compared to participants in the long-term consumption of 1-14 drinks/week group, with no indication of reverse causation. (Sabia et al. 2018)
Potential protective mechanisms are as follows:
1. A reduced risk of cardiovascular disease and type 2 diabetes associated with moderate alcohol consumption. several cardiovascular risk factors are known to be associated with cognitive impairment, and a high haemoglobin A1C level is associated with an increasing risk of diabetes and impaired memory function. In the Whitehall II cohort study, part of the excess risk of dementia in abstainers was attributable to a higher risk of cardio-metabolic diseases such as heart attack, stroke, and type 2 diabetes (Sabia et al. 2018).
2. Alcohol consumption and the glymphatic system. The glymphatic system is a waste clearance pathway of the central nervous system, facilitating the flow of cerebrospinal fluid to the venous perivascular spaces and ultimately clearing waste products from the brain. In recent years, findings from rodent studies have suggested that a decreased glymphatic function leads to accumulation in brain tissue of amyloid-beta and tau ─ the trigger and bullet in the development of Alzheimer’s disease. Other rodent studies’ results have suggested that alcohol has a J-shaped effect on the glymphatic system, whereby low doses of ethanol (0.5 g/kg) increase glymphatic function following acute exposure as well as after one month of chronic exposure. Conversely, acute exposure to 1.5 g/kg alcohol (binge level) dramatically suppressed glymphatic function in mice, which might possibly contribute to the higher risk of dementia observed in heavy drinkers. (Lundgaard et al. 2018)
3. More frequent social contact. Findings from the Whitehall II Cohort Study suggest a protective effect of social contact against dementia, and that more frequent contact confers higher cognitive reserve. However, it is also possible that the ability to maintain more social contact may be a marker of cognitive reserve. (Sommerlad et al. 2019). A review of studies exploring the perceptions and experiences of alcohol use by adults aged 50+ years found that drinking could help sustain social and leisure activity, which may otherwise diminish due to the ageing process (Bareham et al. 2019).
References
Amieva H, Jacqmin-Gadda H, Orgogozo JM, Le Carret N, Helmer C, Letenneur L, Barberger-Gateau P, Fabrigoule C, Dartigues JF. The 9 year cognitive decline before dementia of the Alzheimer type: a prospective population-based study. Brain. 2005; 128(Pt 5:1093-101.
Attems J, Jellinger KA. The overlap between vascular disease and Alzheimer’s disease–lessons from pathology. BMC Med. 2014 Nov 11;12:206. doi: 10.1186/s12916-014-0206-2.
Bareham BK, Kaner E, Spencer LP, Hanratty B. Drinking in later life: a systematic review and thematic synthesis of qualitative studies exploring older people’s perceptions and experiences. Age Ageing. 2019 Jan 1;48(1):134-146. doi: 10.1093/ageing/afy069.
Britton A, Singh-Manoux A, Marmot M. Alcohol consumption and cognitive function in the Whitehall II Study. Am J Epidemiol. 2004 Aug 1;160(3):240-7. doi: 10.1093/aje/kwh206.
Chen Y, Yin X, Wang X, Zheng X, Yang X, Zhou J, Shi M, Zhang Y. Associations of alcohol drinking with incident dementia: a prospective study from the UK Biobank. Eur J Epidemiol. 2025; published online Sept 27. doi:10.1007/s10654-025-01304-y.
Commenges D, Scotet V, Renaud S, Jacqmin-Gadda H, Barberger-Gateau P, Dartigues JF. Intake of flavonoids and risk of dementia. Eur J Epidemiol. 2000; 16:357-363.
Elias PK, Elias MF, D’Agostino RB, Silbershatz H, Wolf PA. Alcohol consumption and cognitive performance in the Framingham Heart Study. Am J Epidemiol. 1999 Sep 15;150(6):580-9. doi: 10.1093/oxfordjournals.aje.a010056.
Ellison RC, Grønbæk M, Skovenborg E. Using Mendelian Randomization to Evaluate the Effects of Alcohol Consumption on the Risk of Coronary Heart Disease. Drugs & Alcohol Today 2021; 21:84-95. https://doi.org/10.1108/DAT-09-2020-0061:
Ferri CP, Prince M, Brayne C, Brodaty H, Fratiglioni L, Ganguli M, Hall K, Hasegawa K, Hendrie H, Huang Y, Jorm A, Mathers C, Menezes PR, Rimmer E, Scazufca M. Alzheimer’s Disease International. Global prevalence of dementia: a Delphi consensus study. Lancet. 2005; 366(9503):2112-2117.
den Heijer T, Vermeer SE, van Dijk EJ, Prins ND, Koudstaal PJ, van Duijn CM, Hofman A, Breteler MM. Alcohol intake in relation to brain magnetic resonance imaging findings in older persons without dementia. Am J Clin Nutr. 2004 Oct;80(4):992-7. doi: 10.1093/ajcn/80.4.992.
Kelner KL, Marx J. Patterns of aging. Science. 1996; 273:41. doi: 10.1126/science.273.5271.41
Kalev-Zylinska ML, During MJ. Paradoxical facilitatory effect of low-dose alcohol consumption on memory mediated by NMDA receptors. J Neurosci. 2007 Sep 26;27(39):10456-67. doi: 10.1523/JNEUROSCI.2789-07.2007.
Kalmijn S, van Boxtel MP, Verschuren MW, Jolles J, Launer LJ. Cigarette smoking and alcohol consumption in relation to cognitive performance in middle age. Am J Epidemiol. 2002 Nov 15;156(10):936-44. doi: 10.1093/aje/kwf135.
Lopez AD, Williams TN, Levin A, Tonelli M, Singh JA, Burney PG, Rehm J, Volkow ND, Koob G, Ferri CP. Remembering the forgotten non-communicable diseases. BMC Med. 2014 Oct 22;12:200. doi: 10.1186/s12916-014-0200-8.
Lundgaard I, Wang W, Eberhardt A, Vinitsky HS, Reeves BC, Peng S, Lou N, Hussain R, Nedergaard M. Beneficial effects of low alcohol exposure, but adverse effects of high alcohol intake on glymphatic function. Sci Rep. 2018 Feb 2;8(1):2246. doi: 10.1038/s41598-018-20424-y.
Lutz W, Sanderson W, Scherbov S. The coming acceleration of global population ageing. Nature. 2008 Feb 7;451(7179):716-9. doi: 10.1038/nature06516.
Mukamal KJ, Longstreth WT Jr, Mittleman MA, Crum RM, Siscovick DS. Alcohol consumption and subclinical findings on magnetic resonance imaging of the brain in older adults: the cardiovascular health study. Stroke. 2001 Sep;32(9):1939-46. doi: 10.1161/hs0901.095723.
Neafsey EJ, Collins MA. Moderate alcohol consumption and cognitive risk. Neuropsychiatr Dis Treat. 2011;7:465-84. doi: 10.2147/NDT.S23159.
Olanow CW. The pathogenesis of cell death in Parkinson’s disease–2007. Mov Disord. 2007 Sep;22 Suppl 17:S335-42. doi: 10.1002/mds.21675.
Orgogozo JM, Dartigues JF, Lafont S, Letenneur L, Commenges D, Salamon R, Renaud S, Breteler MB. Wine consumption and dementia in the elderly: a prospective community study in the Bordeaux area. Rev Neurol (Paris). 1997 Apr;153(3):185-92.
Rehm J, Hasan OSM, Black SE, Shield KD, Schwarzinger M. Alcohol use and dementia: a systematic scoping review. Alzheimers Res Ther. 2019 Jan 5;11(1):1. doi: 10.1186/s13195-018-0453-0.
Rushworth JV, Griffiths HH, Watt NT, Hooper NM. Prion protein-mediated toxicity of amyloid-β oligomers requires lipid rafts and the transmembrane LRP1. J Biol Chem. 2013 Mar 29;288(13):8935-51. doi: 10.1074/jbc.M112.400358.
Sabia S, Fayosse A, Dumurgier J, Dugravot A, Akbaraly T, Britton A, Kivimäki M, Singh-Manoux A. Alcohol consumption and risk of dementia: 23 year follow-up of Whitehall II cohort study. BMJ. 2018 Aug 1;362:k2927. doi: 10.1136/bmj.k2927.
Smith MA, Perry G. Free radical damage, iron, and Alzheimer’s disease. J Neurol Sci. 1995 Dec;134 Suppl:92-4. doi: 10.1016/0022-510x(95)00213-l.
Sommerlad A, Sabia S, Singh-Manoux A, Lewis G, Livingston G. Association of social contact with dementia and cognition: 28-year follow-up of the Whitehall II cohort study. PLoS Med. 2019 Aug 2;16(8):e1002862. doi: 10.1371/journal.pmed.1002862.
Steinman J, Sun HS, Feng ZP. Microvascular Alterations in Alzheimer’s Disease. Front Cell Neurosci. 2021 Jan 18;14:618986. doi: 10.3389/fncel.2020.618986.
Tarawneh R. Microvascular Contributions to Alzheimer Disease Pathogenesis: Is Alzheimer Disease Primarily an Endotheliopathy? Biomolecules. 2023 May 13;13(5):830. doi: 10.3390/biom13050830
Thambisetty M, Varma V, An Y, Mahajan, U, Oommen A, Varma S, Troncoso, J, Pletnikova O, Legido-Quigley C, Elsevier BV. The new neurobiology of dementia. J Neurological Sci. 2019. 405:37–38.
Topiwala A, Levey DF, Zhou H, Deak JD, Adhikari K, Ebmeier KP, Bell S, Burgess S, Nichols TE, Gaziano JM, et al. Alcohol use and risk of dementia in diverse populations: evidence from cohort, case-control and Mendelian randomisation approaches. BMJ Evid Based Med. 2025; published online Sept 16. doi:10.1136/bmjebm-2025-113913.
The following International Scientific Forum on Alcohol Research members provided comments on this critique:
Creina Stockley, PhD, MBA, Independent consultant and Adjunct Senior Lecturer in the School of Agriculture, Food and Wine at the University of Adelaide, Australia
Henk Hendriks, PhD, Independent consultant and partner of the Nutrition Consultants Cooperative, Netherlands
R. Curtis Ellison, MD, Section of Preventive Medicine/Epidemiology, Boston University School of Medicine, Boston, MA, USA
Richard Harding, PhD, Formerly Head of Consumer Choice, Food Standards and Special Projects Division, Food Standards Agency, UK
Tedd Goldfinger, PhD, Formerly Head of Consumer Choice, Food Standards and Special Projects Division, Food Standards Agency, UK
Arne Svilaas, MD, PhD, general practice and lipidology, Oslo University Hospital, Oslo, Norway
Fulvio Ursini, MD, Emeritus Professor of Biochemistry, University of Padova, Padova, Italy
Monika Christmann, PhD, Head of Institute, Department of Enology and Professorship for Enology, Hochschule Geisenheim University, Germany
Giovanni de Gaetano, MD, PhD, Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo NEUROMED, Pozzilli, Italy
Andrew Waterhouse, PhD, Department of Viticulture and Enology, University of California, Davis, USA
Dominique Lanzmann-Petithory, MD, PhD, Nutrition/Cardiology, Praticien Hospitalier Hôpital Emile Roux, Paris, France
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