Circulating metabolites may illustrate relationship of alcohol consumption with cardiovascular disease

In this present study, we investigated the associations between the cumulative average alcohol consumption and 211 circulating metabolites in the 2428 FHS participants. Of the 211 metabolites, the cumulative average alcohol consumption was associated with 60 metabolites. We found that nine metabolites were more strongly associated with a specific type of alcoholic beverage. We also found that the cumulative average total alcohol consumption displayed stronger associations with 13 metabolites in women than men. Furthermore, we created two alcohol consumption-associated metabolite scores and showed that they had comparable but opposite association with incident CVD. Taken together, with targeted metabolomic profiling, our study identified a series of alcohol consumption-associated circulating metabolites, and via these metabolites, alcohol consumption may have counteractive effects on CVD risk.

Our results showed that higher level of alcohol consumption was associated with higher plasma levels for about two-thirds of the 60 significant metabolites. Among the top positively associated metabolites were cholesteryl esters (e.g., CE16:1 and CE20:5), phosphatidylcholine (e.g., PC 32:1), and lysophosphatidylcholine (e.g., LPC 20:5). In addition, we observed that 14 plasma triacylglycerols (TAGs) were significantly associated with total alcohol consumption. Among alcohol-related TAGs, six (TAG 52:3, TAG 52:4, TAG 52:5, TAG 54:3, TAG 54:4, and TAG 54:5) displayed negative associations with alcohol consumption (i.e., lower alcohol consumption was associated with higher levels of TAGs) while eight (TAG 46:0, TAG 48:0, TAG 48:1, TAG 50:1, TAG 50:2, TAG 58:10, TAG 58:11, and TAG 60:12) displayed positive associations with alcohol consumption. TAGs emerge as biomarkers of a liver-to-β-cell axis that links hepatic β-oxidation to β-cell functional mass and insulin secretion in pancreas [30]. TAGs are broken into glycerol and free fatty acids in the process of lipolysis, and free fatty acids are either processed by beta-oxidation or converged to ketone [31]. In our association analyses between alcohol-associated metabolites and incident CVD, we showed that six TAGs (TAG 50:2, TAG 50:1, TAG 48:1, TAG 48:0, TAG 46:0, and TAG 52:3) were associated with incident CVD using the base models. Specifically, PC 32:1 and TAG 48:0 were positively associated with HF. In addition, TAG 52:3 was positively associated with both MI and CHD. Furthermore, TAG 50:1 and TAG 50:2 were positively associated with both HF and CHD. Among these six TAGs, the association remained significant (p < 0.05) with CVD for TAG 50:2, TAG 50:1, and TAG 48:1 after adjusting for common cardiometabolic CVD risk factors. However, likely due to the reduced number of cases for each CVD subtype (relative to the analysis using the composite incident CVD as the outcome variable), our multivariable analysis may lack sufficient statistical power. Therefore, we observed that additional adjustment for common cardiometabolic CVD risk factors attenuated associations with CVD subtypes (p > 0.05). Overall, these observations are in line with the well-known effects of alcohol intake on lipid metabolism [32].

Alcohol consumption was also associated with several types of circulating metabolites, other than TAGs. For example, we showed that alcohol consumption was associated with reduced levels of dimethylglycine. Dimethylglycine plays an important role in one-carbon metabolism as a methyl donor [33, 34]. This function may be related to our previous observations regarding the strong correlation of alcohol consumption with DNA methylation [22]. Nonetheless, the extent to which alcohol consumption affects the source of one-carbon metabolism and the subsequent impact on the risk of developing CVD warrant further investigation.

Among the metabolites that were negatively associated with alcohol consumption, valine, isoleucine, and leucine are branched-chain amino acids (BCAA). A recent review summarized the complex relationship between impaired BCAA homeostasis to CVD [35]. Several lines of evidence suggest that higher BCAA levels are associated with increased risk of obesity and diabetes, which is consistent with the present observations on the positive association of leucine and isoleucine with incident CVD. Nonetheless, future studies in larger sample size and diverse populations are needed to examine the relationships between alcohol consumption, BCAA, and CVD. Several lines of evidence suggest that higher BCAA levels are associated with increased risk of obesity and diabetes, e.g., Ho’s study demonstrated positive associations between BCAA levels and BMI, fasting glucose, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in the same FHS participants [17]. These data are consistent with our previous findings on the inverse associations of alcohol consumption with obesity and type 2 diabetes [21], as well as the observations on the positive association of leucine and isoleucine with incident CVD in the present study. BCAAs are nitrogen donors for hepatic gluconeogenesis [36]. Our observations may support the notion that alcohol consumption, mainly moderate consumption, suppresses gluconeogenesis via lowering BCAA levels and subsequently controlling blood glucose to maintain normoglycemia. Nonetheless, future studies with larger sample sizes and diverse populations are needed to validate our observations, and experimental studies and clinical trials are needed to examine the relationships between alcohol consumption, BCAA, and CVD risk.

Our observations also highlight the complex relationship between alcohol consumption and circulating metabolites, which was demonstrated by the analysis using the two metabolite scores. Our observations suggest that, via circulating metabolites, alcohol drinking may have both positive and negative effects on CVD, and the two effects seemed to cancel each other out in our study samples. However, if certain factors disrupt the balance, it is possible that one effect may prevail over the other effect and leads to either increased or decreased risk of developing CVD. As such, future studies are warranted to understand what factors may modify the association of alcohol consumption and circulating metabolites, as well as their impact on the relationship of alcohol consumption with CVD development.

We observed that wine consumption and liquor had stronger associations with TAG, CE, and SM lipid metabolites, while beer had stronger associations with PC lipid metabolites. We also found that wine and liquor had different associations with amino acids, quinoline carboxylic acids, and hydroxy acids. Liquor consumption was significantly related to higher levels of 3-ureidopropionic acid, whereas wine consumption had stronger association with betaine, 2-hydroxyglutaric acid, xanthurenate, isoleucine, and valine compared to liquor. These observations suggest that consumption of different types of alcoholic beverages are associated with different metabolomic responses. However, the observed associations may also be driven by confounders such as unmeasured components in different alcoholic beverages or dietary and other environmental factors that were not adjusted for in the present analysis. Some of these metabolites such as betaine and isoleucine [35, 37] may play important roles in CVD development. Perhaps due to the short list of metabolites examined, the present study did not support the notion that a certain type of alcohol may bring specific benefits to reduce CVD risk. Future studies including a comprehensive list of metabolites are warranted to investigate this issue.

It was found by van Roekel et al. that total alcohol intake was associated with 34 circulating metabolites, including 3 acylcarnitines, the amino acid citrulline, 4 lysophosphatidylcholines, 13 diacylphosphatidylcholines, 7 acyl-alkylphosphatidylcholines, and 6 sphingomyelins [12] among middle-aged (mean age = 58.3) participants in European Prospective Investigation into Cancer and Nutrition Cohort. Among the 34 metabolites significant in the van Roekel’s study, 13 metabolites were also measured by our metabolite platforms, including LPC 16:0, LPC 16:1, LPC 20:4, PC 32:0, PC 32:1, PC 32:2, PC 34:1, PC 34:3, PC 34:4, PC-B 36:4, PC 38:6, PC 32:1, and SM 24:1. All of the 13 metabolites were significant in our analysis for total alcohol consumption (Additional file 7: Fig. S7, Additional file 16: Table. S9).

In a cross-sectional analysis, Würtz et al. examined the association of alcohol intake with 76 metabolites among young adults (aged 25–45) [38]. In that study, 36 metabolites were considered significantly associated with alcohol consumption. Of these 36 metabolites, 11 metabolites (glutamine, glycine, alanine, isoleucine, leucine, valine, lactate, pyruvate, glycerol, citrate, and creatinine) were also included in the present study, and 3 of 11 metabolites (glutamine, glycerol and leucine) reached significance using our data (Additional file 17: Table. S10). Glutamine and glycerol displayed similar association across the two cohorts. Interestingly, compared to our findings, the Würtz et al. study showed an opposite association between total alcohol consumption and leucine. Leucine is one member of the second metabolite score in the present study, which was inversely associated with incident CVD. As such, this observation may echo our abovementioned hypothesis that certain unknown factor(s) may modify the alcohol–metabolite association in different study samples. In addition, six metabolites (glutamine, glycine, alanine, isoleucine, leucine, valine) were included in all three studies (the Würtz et al. study, the van Roekel’s study, and the present study). Four of the six common metabolites were significant in our study and three of them were significant in Würtz et al.’s study, but none of them were significant in van Roekel’s study (Additional file 17: Table. S10). Together, these observations highlight the need for future studies to comprehensively investigate the heterogeneity with respect to alcohol–metabolite associations in different populations using harmonized metabolite panels.

We observed that, for 13 metabolites, their association strength with alcohol consumption was stronger in women compared to that in men. Women generally have smaller body sizes; consuming the same amount of alcohol would end up with a higher blood alcohol concentration for an average woman compared to an average man. In addition, women may have greater ethanol clearance than men, given the same lean body mass [39]. This may, at least partly, explain our observation with respect to the stronger metabolite response in women. Whether the observed sex–alcohol interaction can be affected by other factors, as well as its impact on CVD and clinical outcomes, may need future investigations.

Strengths and limitations of the study

Our study had several strengths. The most important advantage was that alcohol drinking data from five exams across around 20 years were utilized in the current study. Our study had several limitations. Because of the observational nature of our findings and no experimental validation, causality cannot be inferred. Despite that the sample size in our study was large, the population was primarily white, middle-aged participants. Therefore, the findings from our study may not be generalizable to populations of different races and age groups. As shown in Additional file 1: Fig. S1, cumulative average consumption is a good proxy for long-term alcohol consumption. However, the analysis using total alcohol consumption at exam 5 yielded a similar alcohol–metabolite association. This observation may be driven by the possibility that many of our study participants maintained a low-to-moderate alcohol drinking habit. Future studies are needed to validate our findings in other populations with longitudinal alcohol measurements. Alcohol consumption was measured by questionnaires and calculated based on standard serving size. This approach is cost-effective; however, measurement errors may bias the observed association between alcohol intake and metabolite levels. We acknowledge that the metabolites data analyzed in our study are comprised of a targeted panel. Association between alcohol drinking and untargeted metabolites remained to be studied. Research utilizing metabolite platforms including those from exogenous sources, e.g., ethyl glucuronide and derivates of resveratrol, are needed to better understand the alcohol–metabolite relationship. We observed that sex may modify the association between total alcohol consumption and metabolite levels. Several other factors may also modify the observed associations. For example, the presence or absence of food in the stomach can change the rate of alcohol absorption and metabolism [40, 41] and subsequently affect the association of alcohol consumption with circulating metabolite profiles. In addition, the use of average alcohol consumption in the present analysis may not reflect participants’ diverse drinking patterns. For example, the information on alcohol consumption patterns such as drinking alcohol with or without meals or weekend binge drinking was not collected. Participants’ genetic background is a key factor that may modify alcohol metabolism [42], which may need further studies with larger sample size.