==== Front BMC Cardiovasc Disord BMC Cardiovasc Disord BMC Cardiovascular Disorders 1471-2261 BioMed Central London 1787 10.1186/s12872-020-01787-5 Research Article The effect of ALDH2 rs671 gene mutation on clustering of cardiovascular risk factors in a big data study of Chinese population: associations differ between the sexes Wang Danchen 1 Zou Yutong 1 Yu Songlin 1 Lin Songbai 2 Li Honglei 1 Yin Yicong 1 http://orcid.org/0000-0002-0734-8144Qiu Ling lingqiubj@163.com 1 Xu Tengda Xutd@pumch.cn 2 Wu Jie wuj8289@163.com 1 1 Department of Laboratory Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifu Yuan, Dongcheng District, Beijing, 100730 China 2 Department of Health Care, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, No. 1 Shuaifu Yuan, Dongcheng District, Beijing, 100730 China 4 12 2020 4 12 2020 2020 20 5091 8 2020 18 11 2020 © The Author(s) 2020Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Background The ALDH2 rs671 genetic polymorphism has been linked with cardiovascular diseases (CVDs), but comprehensive epidemiological studies are lacking. An observational, retrospective big data study was carried out to evaluate the associations between this polymorphism and clustering cardiovascular risk factors (CRFs) in a Chinese population. Methods A total of 13,101 individuals (8431 males and 4670 females) were enrolled. Genetic polymorphism was assessed using gene mutation detection kits, coupled with an automatic fluorescent analyzer. Other data were obtained from the records of the Department of Health Care at Peking Union Medical College Hospital. Results Comparing the concentrations of common biochemical analytes, including BMI, SBP, DBP, ALT, AST, γ-GT, TBil, Cr, Glu, TC, TG, and HDL-C among individuals with the GG, GA, and AA genotypes of ALDH2 rs671, we found significant differences in males (all p < 0.001), but not in females. For males, the frequencies of hypertension, diabetes, and obesity were significantly higher for GG than for GA or AA (all p < 0.05). However, there was no significant difference for dyslipidemia, and no significant associations were observed for all frequencies in females. The prevalence of individuals with 1–4 CRFs was significantly higher among GG males than those carrying GA or AA, and fewer GG males had non-CRFs (all p < 0.05). Conclusion Polymorphisms of ALDH2 rs671 are associated with clustering CRFs, especially hypertension and diabetes in males, but not in females. These associations are likely mediated by alcohol intake, which is also associated with this gene. Keywords ALDH2rs671Cardiovascular diseaseCardiovascular risk factorKey Research and Development Program of Ningxia2018BFG02010Qiu Ling CAMS Innovation Fund for Medical SciencesCIFMS-2018-I2M-AI-005Xu Tengda National Basic Research Program of China (973 Program) (CN)2020-1-4014Qiu Ling issue-copyright-statement© The Author(s) 2020 ==== Body Background Cardiovascular diseases (CVDs) is one of the leading causes of mortality worldwide [1, 2], with more than 55 million deaths caused by CVDs in 2017 [3]. Hypertension, diabetes, obesity, and dyslipidemia are well known as cardiovascular disease risk factors (CRFs) [4–7]. CRFs are common, carry an increased risk of CVDs, and their prevalence increases with age [1]. Moreover, the effect of clustering CRFs is greater than the effect of single CRFs on the same individual [2]. Alcohol is one of the most widely used recreational substances worldwide, and its intake is a leading risk factor for global disease burden, including CVDs [4–7]. Despite general recognition that alcohol intake has a negative effect on health, it has been estimated that the average ethanol consumption of a person aged more than 15 years is approximately 19.7 mL per day [8]. Other data suggest that global adult per-capita consumption is estimated to increase from 6.5 L (95% CI: 6.0 l–6.9 L) in 2017 to 7.6 L (95% CI: 6.5–10.2 L) by 2030 [9]. As an essential bioactivating enzyme, ALDH2 can degrade acetaldehyde to nontoxic acetic acid. It is encoded by the ALDH2 gene, which is commonly polymorphic in East Asian populations [5]. It has been reported that as many as 30–50% of East Asians carry an inactive form of ALDH2-rs671 resulting from a single G-to-A transition causing replacement of glutamate to lysine at position 504, and drastically reducing the carrier’s capacity to metabolize alcohol [10–12]. The frequency of the A allele was reported to be 0.21 in China [13]. ALDH2 activation has also been found to be associated with improved mitochondrial function and the remodeling of ventricular function [14, 15], and many studies have reported an association between ALDH2 and CVDs [1, 2, 5, 13, 15, 16]. The most important known feature of the myocardial cardio-protective role of ALDH2 is the clearance of toxic aldehydes such as 4-hydroxynonenal and its adducts, which can be induced by acute oxidative stress upon cardiac ischemia or reperfusion [17–19]. Activation of ALDH2 may slow down the progression of atherosclerosis via attenuation of endoplasmic reticulum stress and apoptosis in smooth muscle cells [16]. Genetic association studies have recently shown that the ALDH2 rs671 polymorphism is a significant risk factor for hypertension, diabetes, and coronary heart diseases in Asian people [20, 21]. Although a number of studies have focused on the association between ALDH2 and single CRFs such as hypertension, diabetes, obesity, and dyslipidemia, and analyses [20, 21], the association has not been clearly defined. Thus, detailed studies focused on the association between ALDH2 and clustering CRFs are needed. Interestingly, there is an increasing interest in obtaining annual routine physical examination in China, which has resulted in more data on the health status of the population. Using data from hospital and laboratory information systems is not only cost-effective but also efficient. Therefore, this retrospective study, which is based on clinical big data, aimed to (1) evaluate the distribution of ALDH2 rs671 genotypes, (2) evaluate the prevalence of single and clustering CRFs in China, and (3) explore the association between ALDH2 rs671 genotypes and CRFs. Methods Data collection The study included 13,101 patients aged ≥19 years old. Data including demographic information, common biochemical analytes, and medical history from November, 2013 to October, 2018, were obtained from the hospital information system (HIS) and laboratory information system (LIS) of the Department of Health Care at Peking Union Medical College Hospital (PUMCH). With a unique identification code identifying duplicated measurements, only the first record of each person was saved. Laboratory measurement Genomic DNA was extracted from whole peripheral blood via DNA extraction kits (Tianlong Technology Co. LTD, Xi’an, China) and rs671 polymorphism status was determined by an ALDH2 gene mutation detection kit, coupled with an automatic fluorescent analyzer (Beijing market gene technology Co. LTD, Beijing, China). Height, weight, and blood pressure were measured by well-trained nurses and doctors, and body mass index (BMI) was calculated as weight divided by height squared. Common biochemical analytes including Albumin (Alb), alanine aminotransferase (ALT), Aspartate aminotransferase (AST), glutamyl transpeptidase (γ-GT), total bilirubin (TBil), creatinine (Cr), glucose (Glu), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), and low density lipoprotein cholesterol (LDL-C) were measured by a Roche C8000 automatic analyzer (Roche C8000, Basel, Switzerland) with corresponding reagents, calibrators, and quality control materials. All records including quality control and external quality assessment during this period were reviewed and deemed sound. Definition of cardiovascular disease risk factors (CRFs) In this study, we evaluate the association between the ALDH2 rs671 polymorphism and major CRFs including hypertension, diabetes, obesity, and dyslipidemia. We used the following specific definitions, as previously described [22]:Hypertension: systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg [23]. Diabetes: fasting blood Glu ≥7 mmol/L or HbA1C ≥6.5%. Obesity: BMI ≥28 kg/m2. Dyslipidemia: at least one of the following: TC ≥5.2 mmol/L, TG ≥1.7 mmol/L, HDL-C < 1.0 mmol/L, and/or LDL-C ≥ 3. 4 mmol/L. Statistical analysis Excel 2010 (Microsoft Inc., USA), SPSS 20.0 software (SPSS Inc., Chicago, IL, USA), and Graphpad prism for Windows (GraphPad Software, San Diego, CA), were used for our statistical analyses. The Mann-Whitney U or Kruskal-Wallis tests were used to compare measurements among groups, and the comparisons of prevalence were conducted by Chi-square test. Multivariate logistic regression analysis was used to correct for covariates and calculate the odds ratios (ORs), with 95% confidence intervals (CIs), of genotype associations with CRFs. The results were considered statistically significant when the two-sided p-value was < 0.05. Results Basic characteristics of the studied population The baseline demographic and clinical characteristics of studied individuals divided by ALDH2 polymorphism and sex are shown in Table 1. In total, 13,101 individuals including 8431 males and 4670 females were eventually included. The distribution of age was (49 ± 9) years old, and BMI was (24.8 ± 3.8) kg/m2. There was no difference in age by ALDH2 polymorphism in either males or females. However, common clinical measurements including BMI, SBP, DBP, ALT, AST, γ-GT, TBil, Cr, Glu, TC, TG, and HDL-C were significantly different in males (all p < 0.001), though not in females.Table 1 General characteristics of the enrolled population GG GA AA P in male P in female Male (n=5636) Female (n=3255) Male (n=2571) Female(n=1286) Male (n=224) Female (n=129) Age (years) 48 ± 9 49 ± 9 49 ± 9 48 ± 9 48 ± 8 48 ± 9 0.795 0.509 BMI (kg/m2) 25.8 ± 3.6 23.4 ± 3.3 25.4 ± 3.7 23.1 ± 3.7 25.2 ± 4.1 23.3 ± 3.7 < 0.001 0.075 SBP (mmHg) 125.2 ± 15.1 116.3 ± 16.5 122.5 ± 14.7 116.1 ± 18.1 119.5 ± 13.8 117.2 ± 20.2 < 0.001 0.395 DBP (mmHg) 79.2 ± 10.5 69.2 ± 10.1 76.8 ± 9.9 68.5 ± 10.5 74.7 ± 10.0 70.4 ± 11.8 < 0.001 0.060 Alb (g/L) 62.8 ± 2.9 60.6 ± 2.9 62.9 ± 2.9 60.7 ± 2.9 62.6 ± 3.3 61.1 ± 2.9 0.460 0.182 ALT (U/L) 25 (18, 34) 16 (12, 21) 21 (16, 31) 15 (12, 21) 23 (18, 31) 16 (12, 22) < 0.001 0.916 AST (U/L) 20 (17, 25) 18 (15,21) 19 (16, 23) 18 (15,21) 19 (17, 23) 17 (15, 21) < 0.001 0.273 γ-GT (U/L) 36 (24, 60) 16 (12, 23) 28 (20, 43) 16 (12, 23) 24 (18, 35) 15 (12, 25) < 0.001 0.849 Tbil (μmol/L) 11.9 (9.2, 15.3) 9.0 (6.9, 11.9) 11.2 (8.7, 14.5) 8.9 (7.0, 11.5) 10.3 (8.0, 13.9) 9.3 (6.9, 11.7) < 0.001 0.743 Cr (μmol/L) 79.8 ± 13.4 60.4 ± 10.0 81.6 ± 12.4 61.3 ± 22.8 83.0 ± 11.3 59.8 ± 8.7 < 0.001 0.546 Glu (mmol/L) 5.7 ± 1.6 5.2 ± 1.1 5.5 ± 1.4 5.2 ± 1.0 5.4 ± 1.2 5.2 ± 1.3 < 0.001 0.904 TC (mmol/L) 4.82 ± 0.98 4.89 ± 0.92 4.69 ± 0.88 4.88 ± 0.92 4.67 ± 0.85 4.88 ± 1.00 < 0.001 0.890 TG (mmol/L) 1.6 (1.2, 2.4) 1.1 (0.8, 1.6) 1.5 (1.1, 2.2) 1.1 (0.8, 1.6) 1.4 (1.0, 2.1) 1.2 (0.8, 1.6) < 0.001 0.644 HDL-C (mmol/L) 1.11 ± 0.27 1.39 ± 0.33 1.08 ± 0.25 1.38 ± 0.34 1.05 ± 0.23 1.35 ± 0.34 < 0.001 0.398 LDL-C (mmol/L) 3.03 ± 0.81 3.05 ± 0.79 3.00 ± 0.76 3.03 ± 0.79 3.03 ± 0.74 2.96 ± 0.90 0.088 0.243 ALDH2 rs671 genotype frequency by sex and age The distribution of ALDH2 rs671 gene polymorphism among different years (from 2013 to 2018) did not show significant differences (p = 0.946). As Fig. 1 and Supplemental Table 1 show, the frequencies of the ALDH2 rs671 genotypes GG, GA, and AA in the total population were 67.9, 29.4, and 2.7%, respectively. These frequencies did not differ significantly by sex. Although there was no significant difference of the overall age distribution of the different genotypes in either males or females, the frequency of AA in individuals aged ≥65 years old was lower than other age groups in both males and females, with the opposite distribution in evidence for GG. Also, the frequency of GA in those aged between 19 and 29 years was higher than in other age groups, and the frequency of GG was significantly lower (Supplemental Table 1).Fig. 1 The frequency of ALDH2 rs671 genotype by sex Prevalence of CRFs by rs671 genotype The frequencies of CRFs associated with different rs671 genotypes by sex are shown in Table 2. For males, the frequencies of hypertension, diabetes, and obesity were significantly higher for GG than for GA or AA. However, there was no significant difference in the prevalence of dyslipidemia among the three rs671 genotypes. For females, there was no statistically significant difference in the prevalence of hypertension, diabetes, obesity, or dyslipidemia among the rs671 genotypes (all p > 0.05).Table 2 Prevalence of CRFs by rs671 genotype and sex CRFs GG GA AA P in male P in female Male Female Male Female Male Female Hypertension 2662 (47.2%) 621 (19.1%) 992 (38.6%) 245 (19.1%) 66 (29.5%) 34 (26.4%) < 0.001 0.118 Obesity 1320 (23.4%) 276 (8.5%) 501 (19.5%) 113 (8.8%) 42 (18.8%) 15 (11.6%) < 0.001 0.450 Diabetes 791 (14.0%) 170 (5.2%) 279 (10.9%) 78 (6.1%) 26 (11.6%) 10 (7.8%) < 0.001 0.284 Dyslipidemia 4030 (71.5%) 1614 (49.6%) 1807 (70.3%) 655 (50.9%) 152 (67.9%) 63 (48.8%) 0.300 0.693 Prevalence of clustering CRFs by rs671 polymorphism The non-CRFs were defined as individuals who did not have hypertension, obesity, diabetes, or dyslipidemia. The frequencies of non-CRFs were 15.3, 40.9, and 24.4% in males, females, and the total population. The respective frequencies of individuals with one, two, three, and four CRFs were 36.9, 32.4, 12.8, and 2.5% in males, 40.0, 14.7, 3.9, and 0.6% in females. The major cluster of CRFs comprised hypertension, diabetes, obesity, and dyslipidemia. The frequencies of clustering CRFs by rs671 genotype and sex are shown in Table 3. The sex-stratified frequencies of clustered CRFs among the rs671 genotypes were significantly different in males, but not in females. The frequencies of individuals with two, three, and four CRFs were significantly higher in the population with GG than in those with GA or AA in males, while among males with no CRFs, the frequency of GG was statistically lower than GA or AA. However, there was no significant difference between the frequencies of clustering CRFs and ALDH2 genotype in females.Table 3 Prevalence of clustering CRFs by rs671 genotype and sex CRFs GG GA AA P in male P in female Male Female Male Female Male Female CRF = 0 797 (14.1%) 1335 (41.0%) 449 (17.5%) 521 (40.5%) 42 (18.8%) 52 (40.3%) < 0.001 0.946 CRF = 1 1993 (35.4%) 1311 (40.3%) 1019 (39.6%) 513 (39.9%) 101 (45.1%) 42 (32.6%) < 0.001 0.214 CRF = 2 1895 (33.6%) 478 (14.7%) 782 (30.4%) 185 (14.4%) 58 (25.9%) 25 (19.4%) 0.002 0.309 CRF = 3 782 (13.9%) 110 (3.4%) 276 (10.7%) 60 (4.7%) 19 (8.5%) 10 (7.8%) < 0.001 0.008 CRF = 4 168 (3.0%) 21 (0.6%) 41 (1.6%) 7 (0.5%) 3 (1.3%) 0 (0%) 0.001 0.622 Multivariate logistic regression analysis Multivariate logistic regression analysis results are shown in Table 4. This analysis estimated OR with 95% CI for each variable, while adjusting for age and other risk factors. Compared with GG, males with GA and AA were less likely to have hypertension (GA: OR = 0.77, 95% CI: 0.69–0.85; AA: OR = 0.56, 95% CI: 0.41–0.75). Also, males with GG were more likely to have diabetes than those with GA (OR = 0.73, 95% CI: 0.62–0.87). There were no differences in overweight or dyslipidemia among male populations with GG, GA, and AA. For females, there was no significant difference among genotypes in hypertension, diabetes, obesity, or dyslipidemia. In males, though not in females, the proportions of GA and AA decreased with increasing numbers of CRFs.Table 4 Multivariate logistic regression analysis CRFs GG GA AA OR LL UL OR LL UL Male  Hypertension 1(ref) 0.77 0.69 0.85 0.56 0.41 0.75  Diabetes 1(ref) 0.73 0.62 0.87 0.79 0.47 1.32  Overweight 1(ref) 0.88 0.74 1.05 0.95 0.56 1.59  Dyslipidemia 1(ref) 1.05 0.94 1.16 1.00 0.75 1.34  CRFs = 1 1(ref) 0.95 0.83 1.08 0.93 0.66 1.31  CRFs = 2 1(ref) 0.72 0.63 0.83 0.46 0.31 0.69  CRFs = 3 1(ref) 0.59 0.48 0.73 0.40 0.21 0.77  CRFs = 4 1(ref) 0.40 0.22 0.71 0.57 0.13 2.38 Female  Hypertension 1(ref) 1.04 0.87 1.24 1.55 1.01 2.40  Diabetes 1(ref) 1.17 0.83 1.66 1.41 0.61 3.25  Overweight 1(ref) 1.06 0.75 1.49 1.57 0.72 3.41  Dyslipidemia 1(ref) 1.12 0.97 1.28 0.97 0.67 1.41  CRFs = 1 1(ref) 1.06 0.92 1.23 0.95 0.62 1.45  CRFs = 2 1(ref) 1.02 0.82 1.27 1.88 1.12 3.16  CRFs = 3 1(ref) 1.71 1.13 2.59 1.54 0.52 4.60  CRFs = 4 1(ref) 1.04 0.27 3.97 Non Non Non Discussion Based on the distribution of age, the enrolled individuals fairly reflected the distribution of Chinese adults, the frequency of GA, AA and AA during the whole 5 years was 29.4, 2.7 and 17.4%, similar to those of previous studies [13, 24]. The distribution of ALDH2 rs671 gene polymorphism among different years (from 2013 to 2018) did not show significant differences (p = 0.946), which implied the reliability of the measurements without obvious carry-over. ALDH2 activation, which plays key roles in clearing toxic aldehydes, improving mitochondrial function, and remodeling ventricular function, has been shown to be protective against the development of CVDs [14–19, 25], suggesting that ALDH2 gene mutation should be harmful for human health. However, the results of clinical trials have been inconsistent, with many of them indicating a protective effect of the A allele against hypertension, dyslipidemia, and diabetes [3, 4, 21, 26]. In this study, we found that the A allele may be more likely to be protective against clustering CRFs, especially hypertension and diabetes in males, though not in females. The contradictory results between basic research and clinical studies, and between males and females, could be explained by the influence of lifestyles, especially the amount and pattern of alcohol consumption. A study based on the China Kadoorie Biobank reported that 33% of males drank alcohol in most weeks, mainly as spirits, while only 2% of females did so [13]. Because of issues with alcohol tolerance, including uncomfortable feelings such as flush, dizziness, vomiting, and even exhaustion, individuals carrying the A allele, especially those with the AA genotype, usually drink less (GG: 157 g/week; AG: 37 g/week; AA: 3 g/week) [13]. Furthermore, alcohol intake has been found to be closely associated with an increased risk of CVDs [4–7], and reducing alcohol intake can lower blood pressure in a dose-dependent manner [25]. Therefore, it is very likely that the influence of the different ALDH2 rs671 gene polymorphisms on the prevalence of CRFs is substantially mediated by the amount and pattern of alcohol consumption. Interestingly, we also found that the frequency of AA in individuals ≥65 years old was lower than in other age groups, especially 18–29, with p = 0.01, which may imply that the ALDH2 rs671 mutation can induce other mortal diseases and aging independently of CVDs [26, 27]. In this study, we found that, compared with GG carriers, males with GA and AA were less likely to have hypertension. Our results are consistent with a case control study which found that those carrying the A allele were at a lower risk of essential hypertension in males [AA/AG vs. GG: OR (95% CI) = 0.76 (0.58–0.98)], but not in females [21]. However, our results are contrary to a cross-sectional study, which found that the individuals with the rs671 A allele were at higher risk for the development of essential hypertension [28]. In that study, the association was not evaluated separately for males and females, and based on our data, that could have substantially influenced the results. Moreover, our data on the relationship between ALDH2 rs671 genotype and the distributions of TC, TG, and HDL-C, are consistent with previous studies [4, 26, 29]. However, the relationship between rs671 and the prevalence of dyslipidemia as such was not recognized in those studies [4, 26, 29]. Also, we found that the individuals with the rs671 A allele had lower Glu levels and lower prevalence of diabetes, though multivariate logistic regression analysis results didn’t show that the A allele was significantly protective for diabetes in either males or females. This is similar to a previous Mendelian randomization analysis, which showed that the A allele in males was significantly associated with decreased diabetes risk for both the overall population (OR = 0.716, 95% CI: 0.567–0.904, p = 0.005) and moderate drinkers (OR = 0.564, 95% CI: 0.355–0.894, p = 0.015) [30]. Interestingly, another study found that the individuals with the A allele had a lower incidence of microvascular complications associated with alcohol consumption, but a higher incidence of macrovascular complications irrespective of alcohol consumption [31]. This also implied that the incidence of CRFs could be mediated by both genetics and lifestyle factors such as alcohol assumption. Although there have been many other studies exploring and evaluating the association between ALDH2 genotype and many diseases including CVDs and their risk factors, most of them were animal experiments. Epidemiological studies did not emerge until recently, and most have focused on the association between ALDH2 and single CRFs, rather than clustering CRFs. In this study, we derived clinical big data from the HIS and LIS of PUMCH, which was simple, cost-efficient and a good reflection of the general population. With all individuals represented in PUMCH being analyzed over a five-year period by the same analytical systems, variation due different methods or facilitates was avoided, and the demographic information and clinical laboratory measurements were thorough. Furthermore, we were able to analyze hypertension, diabetes, obesity, and dyslipidemia simultaneously, while correcting for covariations via multivariate logistic regression analysis. However, some limitations of this study are notable. Alcohol intake was not considered in the evaluation, and other important factors such as smoking and socioeconomic situation were also lacking. Also, in this cross-sectional study, the major CRFs, including hypertension, diabetes, obesity, and dyslipidemia, were assessed based only on single test of the corresponding clinical measurements. Casual inferences from this study should therefore be avoided. In the future, long term follow-up cohort studies considering more details, especially the pattern of alcohol consumption, are needed to further explore the causal relationships suggested by our data. Conclusion Our study indicates that the ALDH2 gene polymorphism is associated with clustering CRFs, and that the rs671 A allele may be protective against clustering CRFs in males. This is likely mediated by alcohol intake or related lifestyle factors associated with this genetic variant. Supplementary information Additional file 1: Supplemental Table 1. The frequency of ALDH2 rs671 genotype by age and sex. Abbreviations CVDsCardiovascular diseases CRFsCardiovascular disease risk factors ALDH2Aldehyde dehydrogenase 2 HISHospital Information System LISLaboratory Information System PUMCHPeking Union Medical College Hospital BMIBody mass index AlbAlbumin ALTAlanine aminotransferase ASTAspartate aminotransferase TBilTotal bilirubin CrCreatinine GluGlucose TCTotal cholesterol TGTriglyceride HDL-CHigh density lipoprotein cholesterol LDL-CLow density lipoprotein cholesterol SBPSystolic blood pressure DBPDiastolic blood pressure OROdds ratio CIConfidence interval Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Danchen Wang, Yutong Zou and Songlin Yu contributed equally to this work Supplementary information Supplementary information accompanies this paper at 10.1186/s12872-020-01787-5. Acknowledgements None. Authors’ contributions DCW, YTZ, LQ, SLY, and TDX designed the experiment. LQ, DCW, SLY, and TDX analyzed the data. DCW, YTZ, LQ, SLY, HLL, JW, YCY, and SBL were involved in scientific discussion. DCW, YTZ, LQ, TDX, HLL, SLY, JW, and YCY drafted and revised the manuscript. The author(s) read and approved the final manuscript. Funding This study was supported by grants from the Key Research and Development Program of Ningxia [2018BFG02010], and the CAMS Innovation Fund for Medical Sciences (CIFMS-2018-I2M-AI-005). The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Availability of data and materials The datasets generated and analysed during the current study are available from the corresponding author on reasonable request. The datasets generated and/or analysed during the current study are available in the National Center for Biotechnology Information repository, https://www.ncbi.nlm.nih.gov/gene/217. Ethics approval and consent to participate Ethical approval was obtained from the Ethics Committee of Peking Union Medical College Hospital of the Chinese Academy of Medical Sciences (protocol number: S-K1114). All the data obtained was anonymized. The need for consent was waived by the Ethics Committee of Peking Union Medical College Hospital of the Chinese Academy of Medical Sciences. Consent for publication Not applicable. Competing interests None. ==== Refs References 1. Macek P Zak M Terek-Derszniak M Biskup M Ciepiela P Krol H Age-dependent disparities in the prevalence of single and clustering cardiovascular risk factors: a cross-sectional cohort study in middle-aged and older adults Clin Interv Aging 2020 15 161 169 10.2147/CIA.S238930 32103918 2. Palazón-Bru A Ferri-Rufete D Mares-García E Durazo-Arvizu R Divisón-Garrote J Carbayo-Herencia J Clusters of cardiovascular risk factors and their impact on the 20-year cardiovascular risk in a general population J Cardiovasc Nurs 2020 35 2 210 216 10.1097/JCN.0000000000000637 31904694 3. GBD 2017 Causes of Death Collaborators Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017 Lancet 2018 392 10159 1736 1788 10.1016/S0140-6736(18)32203-7 30496103 4. Taylor AE Lu F Carslake D Hu Z Qian Y Liu S Exploring causal associations of alcohol with cardiovascular and metabolic risk factors in a Chinese population using Mendelian randomization analysis Sci Rep 2015 5 14005 10.1038/srep14005 26364564 5. Shin MJ Cho Y Davey Smith G Alcohol consumption, aldehyde dehydrogenase 2 gene polymorphisms, and cardiovascular health in Korea Yonsei Med J 2017 58 4 689 696 10.3349/ymj.2017.58.4.689 28540979 6. Cho Y Shin SY Won S Relton CL Davey Smith G Shin MJ Alcohol intake and cardiovascular risk factors: a Mendelian randomisation study Sci Rep 2015 5 18422 10.1038/srep18422 26687910 7. Zhao D Liu J Xie W Qi Y Cardiovascular risk assessment: a global perspective Nat Rev Cardiol 2015 12 5 301 311 10.1038/nrcardio.2015.28 25754885 8. World Health Organization Global status report on alcohol and health 2018 2018 9. Manthey J Shield KD Rylett M Hasan OSM Probst C Rehm J Global alcohol exposure between 1990 and 2017 and forecasts until 2030: a modelling study Lancet. 2019 393 10190 2493 2502 10.1016/S0140-6736(18)32744-2 31076174 10. Yokoyama A Omori T Yokoyama T Alcohol and aldehyde dehydrogenase polymorphisms and a new strategy for prevention and screening for cancer in the upper aerodigestive tract in East Asians Keio J Med 2010 59 4 115 130 10.2302/kjm.59.115 21187698 11. Yukawa Y Muto M Hori K Nagayoshi H Yokoyama A Chiba T Combination of ADH1B*2/ALDH2*2 polymorphisms alters acetaldehyde-derived DNA damage in the blood of Japanese alcoholics Cancer Sci 2012 103 9 1651 1655 10.1111/j.1349-7006.2012.02360.x 22703580 12. Li H Borinskaya S Yoshimura K Kal'ina N Marusin A Stepanov V Refined geographic distribution of the oriental ALDH2*504Lys (nee 487Lys) variant Ann Hum Genet 2009 73 Pt 3 335 345 10.1111/j.1469-1809.2009.00517.x 19456322 13. Millwood IY Walters RG Mei XW Guo Y Yang L Bian Z Conventional and genetic evidence on alcohol and vascular disease aetiology: a prospective study of 500 000 men and women in China Lancet. 2019 393 10183 1831 1842 10.1016/S0140-6736(18)31772-0 30955975 14. Mali VR Pan G Deshpande M Thandavarayan RA Xu J Yang X Cardiac mitochondrial respiratory dysfunction and tissue damage in chronic hyperglycemia correlate with reduced aldehyde Dehydrogenase-2 activity PLoS One 2016 11 10 e0163158 10.1371/journal.pone.0163158 27736868 15. Gomes KM Campos JC Bechara LR Queliconi B Lima VM Disatnik MH Aldehyde dehydrogenase 2 activation in heart failure restores mitochondrial function and improves ventricular function and remodelling Cardiovasc Res 2014 103 4 498 508 10.1093/cvr/cvu125 24817685 16. Yang MY Wang YB Han B Yang B Qiang YW Zhang Y Activation of aldehyde dehydrogenase 2 slows down the progression of atherosclerosis via attenuation of ER stress and apoptosis in smooth muscle cells Acta Pharmacol Sin 2018 39 1 48 58 10.1038/aps.2017.81 28858301 17. Endo J Sano M Katayama T Hishiki T Shinmura K Morizane S Metabolic remodeling induced by mitochondrial aldehyde stress stimulates tolerance to oxidative stress in the heart Circ Res 2009 105 11 1118 1127 10.1161/CIRCRESAHA.109.206607 19815821 18. Gong D Zhang H Hu S Mitochondrial aldehyde dehydrogenase 2 activation and cardioprotection J Mol Cell Cardiol 2013 55 58 63 10.1016/j.yjmcc.2012.03.017 22507541 19. Liu X Sun A Aldehyde dehydrogenase-2 roles in ischemic cardiovascular disease Curr Drug Targets 2017 18 15 1817 1823 10.2174/1389450117666160912174417 27633387 20. Xia CL Chu P Liu YX Qu XL Gao XF Wang ZM ALDH2 rs671 polymorphism and the risk of heart failure with preserved ejection fraction (HFpEF) in patients with cardiovascular diseases J Hum Hypertens 2020 34 1 16 23 10.1038/s41371-019-0182-2 30846829 21. Wu Y Ni J Cai X Lian FZ Ma HY Xu LW Positive association between ALDH2 rs671 polymorphism and essential hypertension: a case-control study and meta-analysis PLoS One 2017 12 5 e0177023 10.1371/journal.pone.0177023 28472173 22. Li DD Xu T Cheng XQ Wu W Ye YC Guo XZ Serum gamma-glutamyltransferase levels are associated with cardiovascular risk factors in China: a Nationwide population-based study Sci Rep 2018 8 1 16533 10.1038/s41598-018-34913-7 30410032 23. Chobanian AV Bakris GL Black HR Cushman WC Green LA Izzo JL Jr The seventh report of the joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 report JAMA. 2003 289 19 2560 2572 10.1001/jama.289.19.2560 12748199 24. Ma C Yu B Zhang W Wang W Zhang L Zeng Q Associations between aldehyde dehydrogenase 2 (ALDH2) rs671 genetic polymorphisms, lifestyles and hypertension risk in Chinese Han people Sci Rep 2017 7 1 11136 10.1038/s41598-017-11071-w 28894224 25. Vasdev S Gill V Singal PK Beneficial effect of low ethanol intake on the cardiovascular system: possible biochemical mechanisms Vasc Health Risk Manag 2006 2 3 263 276 10.2147/vhrm.2006.2.3.263 17326332 26. Han S Zhao X Zhang X Xu Y Geng J Wang Y Acetaldehyde dehydrogenase 2 rs671 polymorphism affects hypertension susceptibility and lipid profiles in a Chinese population DNA Cell Biol 2019 38 9 962 968 10.1089/dna.2019.4647 31361523 27. Wu NN Ren J Aldehyde dehydrogenase 2 (ALDH2) and aging: is there a sensible link? Adv Exp Med Biol 2019 1193 237 253 10.1007/978-981-13-6260-6_15 31368109 28. Imatoh T Yengo L Rocheleau G Kamimura S Maeda S Miyazaki M ALDH2 polymorphism rs671, but not ADH1B polymorphism rs1229984, increases risk for hypo-HDL-cholesterolemia in a/a carriers compared to the G/G carriers Lipids. 2018 53 8 797 807 10.1002/lipd.12087 30334266 29. Yokoyama A Taniki N Nakamoto N Tomita K Hara S Mizukami T Associations among liver disease, serum lipid profile, body mass index, ketonuria, meal skipping, and the alcohol dehydrogenase-1B and aldehyde dehydrogenase-2 genotypes in Japanese men with alcohol dependence Hepatol Res 2020 50 5 565 577 10.1111/hepr.13475 31845443 30. Peng M Zhang J Zeng T Hu X Min J Tian SS Alcohol consumption and diabetes risk in a Chinese population: a Mendelian randomization analysis Addiction. 2019 114 3 436 449 10.1111/add.14475 30326548 31. Idewaki Y Iwase M Fujii H Ohkuma T Ide H Kaizu S Association of genetically determined aldehyde dehydrogenase 2 activity with diabetic complications in relation to alcohol consumption in Japanese patients with type 2 diabetes mellitus: the Fukuoka Diabetes Registry PLoS One 2015 10 11 e0143288 10.1371/journal.pone.0143288 26599441