Additive Effects of Drinking Habits and a Susceptible Genetic Polymorphism on Cholesterol Efflux Capacity

Abstract

Aims: High levels of high-density lipoprotein cholesterol (HDL-C) are not necessarily effective in preventing atherosclerotic cardiovascular disease, and cholesterol efflux capacity (CEC) has attracted attention regarding HDL functionality. We aimed to elucidate whether drinking habits are associated with CEC levels, while also paying careful attention to confounding factors including serum HDL-C levels, other life style factors, and rs671 (^＊2), a genetic polymorphism of the aldehyde dehydrogenase 2 (ALDH2) gene determining alcohol consumption habit.

Methods: A cross-sectional study was performed in 505 Japanese male subjects who were recruited from a health screening program. Associations of HDL-C and CEC levels with drinking habits and ALDH2 genotypes were examined.

Results: The genotype frequencies of ALDH2 ^＊1/^＊1 (homozygous wild-type genotype), ^＊1/^＊2 and ^＊2/^＊2 (homozygous mutant genotype) were 55%, 37% and 8%, respectively. Both HDL-C and CEC levels were higher in ALDH2 ^＊1/^＊1 genotype carriers than in ^＊2 allele carriers. Although HDL-C levels were higher in subjects who had a drinking habit than in non-drinkers, CEC levels tended to be lower in subjects with ≥ 46 g/day of alcohol consumption than in non-drinkers. Furthermore, CEC levels tended to be lower in ALDH2 ^＊1/^＊1 genotype carriers with a drinking habit of ≥ 46 g/day than non-drinkers, while for ^＊2 allele carriers, CEC levels tended to be lower with a drinking habit of 23-45.9 g/day compared to no drinking habit.

Conclusions: Our results suggest that heavy drinking habits may tend to decrease CEC levels, and in the ALDH2 ^＊2 allele carriers, even moderate drinking habits may tend to decrease CEC levels.

Introduction

Recent epidemiological studies have shown that higher levels of high-density lipoprotein cholesterol (HDL-C) are not necessarily effective in preventing atherosclerotic cardiovascular disease (ASCVD) and extremely high levels of HDL-C lead to greater ASCVD risk^1-3). Moreover, a meta-analysis of randomized controlled trials showed that niacin, fibrates and cholesteryl ester transfer protein (CETP) inhibitors, which increase HDL-C levels, did not reduce all-cause mortality, coronary heart disease mortality, myocardial infarction, or stroke in patients treated with statins⁴⁾. Meanwhile, a Mendelian randomization study showed that genetic polymorphisms associated with lower levels of HDL-C are not related with increased risk of ASCVD⁵⁾. Thus, in recent years, not the quantity, but the functionality of HDL particles has attracted increased attention for verifying the beneficial effects of HDL⁶⁾. HDL plays an important role in cholesterol efflux from peripheral cells to serum, the first step in reverse cholesterol transport, and decreased cholesterol efflux capacity (CEC) has been reported to be associated with the risk of ASCVD^7-9). Although CEC is positively correlated with the amount of HDL-C, CEC varies substantially even with similar HDL-C levels^{6, 10)}. Therefore, improving CEC has recently been considered as a potential target for ASCVD prevention, rather than increasing HDL-C levels^6-10). Furthermore, elucidating the factors associated with inter- and intra-individual variability in CEC should provide useful information for efficiently preventing the development of ASCVD.

The risk of ASCVD was reported to decrease with alcohol intake, primarily in relation to increased HDL-C levels, but the decreasing effect was attenuated by heavy alcohol consumption^11-13). However, the effect of alcohol intake on CEC remains controversial^14-18). An in vitro study showed that the addition of ethanol to rat embryo fibroblasts suppressed cholesterol efflux from the fibroblasts to HDL¹⁴⁾. In humans ex vivo, long-term alcohol intake was found to impair CEC among individuals with chronic alcoholism¹⁵⁾. On the other hand, other clinical studies have reported that alcohol intake is associated with an increase or no change in CEC^16-18). We speculated that the inconsistency in associations between alcohol intake and CEC may be attributable, at least in part, to the frequency, duration and/or amount of alcohol consumed. Drinking behavior and ethanol metabolism are influenced by various factors (e.g., age, sex, genetic background and race)^19-21) and alcohol consumption is also connected with other individual factors (e.g., cigarette smoking and obesity), all of which may affect CEC levels¹⁰⁾. Furthermore, an alcohol-induced quantitative increase in HDL-C levels may obscure the direct effect of alcohol intake on CEC. Therefore, the above confounding factors should be carefully considered in clarifying the relationship between alcohol intake and CEC levels.

Ethanol is metabolized to acetaldehyde mainly by alcohol dehydrogenase (ADH), which is subsequently metabolized to acetic acid by mitochondrial aldehyde dehydrogenase 2 (ALDH2)²²⁾. An allelic variant at rs671 of the ALDH2 gene (i.e., ALDH2 ^＊2) affects drinking behavior by reducing an individual’s alcohol tolerance through a lack of ALDH2 enzyme activity^{21, 22)}. Blood levels of acetaldehyde after alcohol consumption were higher in carriers of the ALDH2 ^＊2 allele than in those of the homozygous wild-type genotype, i.e., ^＊1/^＊1 genotype²³⁾, and thus, ^＊2 allele carriers are more susceptible to alcohol-induced damage²¹⁾. Meanwhile, ALDH2 also plays a key role in detoxifying endogenous toxic aldehydes derived from lipid peroxidation under oxidative stress, including 4-hydroxy-2-nonenal (4-HNE) and malondialdehyde (MDA) as well as environmental aldehydes²¹⁾. Epidemiological studies have shown that the ALDH2 ^＊2 allele was associated with increased risk of coronary artery disease (CAD)²⁴⁾, coronary spastic angina²⁵⁾, ST-segment elevation myocardial infarction²⁵⁾ and diabetic retinopathy²⁶⁾. Furthermore, HDL-C levels have been reported to be lower in carriers of the ALDH2 ^＊2 allele than in those of the ^＊1/^＊1 genotype^{24, 27)}. Based on these observations, the ALDH2 rs671 polymorphism may affect CEC levels through decreased acetaldehyde metabolism and/or drinking behavior but the relationship between ALDH2 rs671 polymorphism and CEC levels remains unclear.

Aim

The present study aimed to determine factors of CEC that could potentially be adjusted to reinforce prevention of ASCVD, by investigating relationships of drinking habits and/or ALDH2 rs671 polymorphism with levels of CEC among Japanese subjects, while also paying careful attention to confounding factors.

Methods

Study Subjects

We retrospectively investigated 865 Japanese subjects who participated in the health screening program. Among them, 360 subjects were excluded for the following reasons: female subjects (n=298) to eliminate gender differences in drinking habits and levels of HDL-C and CEC¹⁰⁾, no plasma available for measuring cholesterol efflux capacity (n=49), no genome DNA available for determining ALDH2 rs671 polymorphism (n=12) and no information available on daily alcohol consumption (n=1). The remaining 505 male subjects (mean age, 62.3±12.6 years) were enrolled in the study (Fig.1).

Fig.1.

Flow chart showing the enrolment of the study subjects

CEC, cholesterol efflux capacity

The sample size of the associations of CEC levels with alcohol consumption and drinking habit categories at a significance (alpha) level of 0.05 (two-tailed) using the expected effect size based on the findings from previous studies^16-18). A power analysis estimated that at least 448 to 500 male subjects would be needed to detect changes in high or low CEC levels due to differences in alcohol consumption or drinking habit categories, and the power of this study were 81 to 84%, exceeding the required power limit (i.e., 80%), and therefore, we included 505 Japanese male subjects in the present study.

This study complied with the principles of the Declaration Helsinki, and the study protocol was approved by the ethics committees of the Faculty of Life Science, Kumamoto University and the National Cerebral and Cardiovascular Center, and the Japanese Red Cross Kumamoto Health Care Center. All study subjects provided written informed consent prior to participating in the study.

Measurements

After approximately 12 hours of fasting, lipid profiles and other biomedical parameters were measured in blood using the standard methods of the Japan Society of Clinical Chemistry at the Japanese Red Cross Kumamoto Hospital Health Center. Information regarding drinking habits and smoking status was obtained via face-to-face interviews with health care providers using a structured questionnaire as described in a previous study²⁸⁾. The ethanol equivalent of alcohol consumption (g/day) was calculated based on the total weekly volume of alcohol intake. In the present study, study subjects were categorized into 4 groups based on alcohol consumption: 1) non-drinkers (who do not drink alcohol even once a week), 2) subjects consuming less than 23 g/day of alcohol, which approximates 2 US standard drinks 3) subjects consuming 23-45.9 g/day of alcohol and 4) subjects consuming 46 g/day or more of alcohol²⁹⁾. Overweight and normal-weight were defined as body mass index (BMI) ≥ 25 kg/m² and BMI ＜25 kg/m², respectively³⁰⁾.

Genotyping

We extracted genomic DNA from the subjects’ whole blood using a DNA purification kit (Flexi Gene DNA kit; QIAGEN, Hilden, Germany), and detected the genetic polymorphism of ALDH2 (rs671) using a real-time TaqMan allelic discrimination assay (assay no. C_11703892_10). We included a positive control (samples that had an already known genotype) and a negative control (water) in each assay to ensure quality.

Assessment of CEC Levels

CEC levels in fasting plasma samples were quantified using the same method as in our previous studies^{31, 32)}. To correct for inter-assay variation across wells, a pooled plasma control sample obtained from healthy volunteer was included in the assessment of CEC levels, and levels for plasma samples from study subjects were normalized to the level of the pooled control sample. In the present study, the CEC level of the pooled control sample was defined as 100.

Assessment of Oxidized Human Serum Albumin

Since the redox state of human serum albumin (HSA) is a sensitive indicator of the progression of chronic diseases related to oxidative stress^{33, 34)}, the current study adopted it as a systemic oxidative stress marker. The redox status of HSA was measured by high-performance liquid chromatography using the same method as in a previous study³⁵⁾. The proportion of the oxidized form of HSA to total HSA was defined as oxidized HSA (%).

Statistical Analyses

Data are expressed as the mean±standard deviation or proportion for categorical variables. Student’s t-test or the Tukey-Kramer method were used to compare the means of continuous variables between groups. Fisher’s exact test was used for comparisons of categorical variables. Pearson correlation analysis was used to detect correlations between two continuous variables. Associations of the HDL-C and CEC levels with the alcohol consumption and drinking habit categories were examined using multiple linear regression analysis with calculation of adjusted unstandardized regression coefficients (B) and standard error (SE) and trend test. Bs were adjusted by age, BMI ≥ 25 kg/m², low-density lipoprotein cholesterol (LDL-C), log-transformed triglycerides (log-TGs), smoking status and ALDH2 genotype for the multiple regression models regarding the levels of HDL-C and CEC (Model 1) or by age, BMI ≥ 25 kg/m², LDL-C, log-TGs, smoking status, HDL-C and ALDH2 genotype only regarding the level of CEC (Model 2). P values for trend tests were adjusted by age, BMI ≥ 25 kg/m², LDL-C levels, log-TGs, smoking status and ALDH2 genotype for the HDL-C levels or by age, BMI ≥ 25 kg/m², LDL-C, log-TGs, smoking status, HDL-C and ALDH2 genotype for the CEC levels. The variables in the bi-variable model were HDL-C and drinking habit or CEC and drinking habit. A P value of ＜0.05 was statistically significant. Multiple comparisons were corrected using Bonferroni’s method, and P values ＜0.05/n were considered to be statistically significant after correcting for the number of comparisons made. All statistical analyses were performed using the SPSS software package (version 23.0, IBM Japan Inc., Tokyo, Japan).

Results

Subject Characteristics

The clinical characteristics of the subjects are shown in Table 1. The frequencies of the ALDH2 ^＊1/^＊1, ^＊1/^＊2 and ^＊2/^＊2 genotypes were 55%, 37% and 8%, respectively. The frequency distribution of the ALDH2 genotypes was consistent with the Hardy–Weinberg equilibrium (P＞0.05). The amount of alcohol consumption (g/day) and the proportions of drinking habit categories differed between the ALDH2 rs671 genotypes (Table 1) as in the case of a previous study³⁶⁾. The values for aspartate aminotransferase (AST), alanine aminotransferase (ALT), γ-glutamyltransferase (GGT), systolic blood pressure (SBP), uric acid (UA) and total bilirubin were higher, and those for TGs and frequency of smokers were lower in carriers of the ALDH2 ^＊1/^＊1 genotype than in those of the ^＊2 allele (Table 1).

Table 1. Clinical characteristics of study subjects

	All (n= 505)	ALDH2 genotype		P value
		＊1/＊1 (n= 277)	＊1/＊2 or ＊2/＊2 (n= 228)
Age (years)	62.3±12.6	62.9±12.7	61.6±12.3	0.252
BMI (kg/m2)	23.4±2.8	23.7±2.8	23.2±2.7	0.055
CEC	81.9±14.2	83.1±14.3	80.5±14.0	0.040
HDL-C (mg/dL)	62.3±15.4	64.6±15.3	59.5±15.1	＜0.001
LDL-C (mg/dL)	119.6±26.8	117.8±26.6	121.7±26.9	0.097
TGs (mg/dL)	97.0 (26-520)	93.0 (30-508)	100.5 (26-520)	0.046†
FBG (mg/dL)	102.8±18.9	103.6±17.9	101.8±20.2	0.284
AST (U/L)	25.4±10.8	26.7±12.7	23.9±7.6	0.002
ALT (U/L)	25.4±15.5	26.8±15.3	23.6±15.6	0.018
GGT (U/L)	43.7±50.5	50.1±62.4	35.8±28.6	0.001
SBP (mmHg)	121.7±16.0	123.1±16.4	120.0±15.5	0.026
DBP (mmHg)	73.6±10.8	74.4±11.2	72.7±10.3	0.078
UA (mg/dL)	5.8±1.3	6.0±1.3	5.6±1.2	0.005
Cr (mg/dL)	0.9±0.2	0.9±0.2	0.9±0.2	0.929
Total bilirubin (mg/dL)	1.0±0.4	1.0±0.4	0.9±0.3	0.039
CRP (mg/dL)	0.1±0.3	0.1±0.2	0.1±0.3	0.180
Albumin (g/dL)	4.5±0.3	4.5±0.3	4.5±0.3	0.239
Oxidized HSA (%)	45.2±3.8	45.0±3.7	45.4±4.0	0.204
Alcohol consumption (g/day)	16.1±18.9	21.5±19.7	9.7±15.6	＜0.001
Drinking habit categories
No drinking habit (%)	159 (31.5)	46 (16.6)	113 (49.6)	＜0.001‡
＜23 g/day (%)	205 (40.6)	124 (44.8)	81 (35.5)
23-45.9 g/day (%)	92 (18.2)	70 (25.3)	22 (9.6)
≥ 46 g/day (%)	49 (9.7)	37 (13.4)	12 (5.3)
Smoking status (%)
Non-smoker (%)	413 (81.8)	240 (86.6)	173 (75.9)	0.002§
Smoker (%)	92 (18.2)	37 (13.4)	55 (24.1)

Values are means±SD, median (range) or number of subjects (%).

^†Mann-Whitney U test. ^‡Chi-square test. ^§Fisher’s exact test (otherwise, Student’s t-test was used).

ALDH2, aldehyde dehydrogenase 2; BMI, body mass index; CEC, cholesterol efflux capacity; HDL-C, high-density lipoprotein cholesterol; LDL- C, low-density lipoprotein cholesterol; TGs, triglycerides; FBG fasting blood glucose; AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, γ-glutamyltransferase; SBP, systolic blood pressure; DBP, diastolic blood pressure; UA, uric acid; CRP, C-reactive protein; Cr, creatinine; HSA, human serum albumin; SD, standard deviation.

Associations of ALDH2 rs671 Polymorphism with Levels of HDL-C and CEC

A positive correlation between HDL-C and CEC levels was observed (Supplemental Fig.1). In the analyses stratified by the ALDH2 genotype, positive correlations between HDL-C and CEC levels were also observed in both ALDH2 ^＊1/^＊1 genotype carriers and ^＊2 allele carriers (Supplemental Fig.1). The levels of both HDL-C and CEC were higher in carriers of the ALDH2 ^＊1/^＊1 genotype than in those of the ^＊2 allele (Table 1, Fig.2). Since drinking habits were affected by the ALDH2 rs671 polymorphism (Table 1), we assessed associations of the ALDH2 genotype with HDL-C and CEC levels stratified according to drinking habits (Fig.2). Among non-drinkers, the levels of both HDL-C and CEC were higher in carriers of the ALDH2 ^＊1/^＊1 genotype than in those of the ^＊2 allele (Fig.2). In contrast, this association was not observed among drinkers (Fig.2). These associations of the ALDH2 gennotype with HDL-C and CEC levels were also observed in the multivariable analyses (Supplemental Table 1).

Supplementary Fig.1.

HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity.

Fig.2. Levels of HDL-C and CEC between ALDH2 genotypes among all subjects, non-drinkers and drinkers

Data shown are mean±SE. P values were calculated by Student’s t-test. HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity; SE, standard error.

Supplemental Table 1. Associations of ALDH2 rs671 polymorphism with levels of HDL-C and CEC

	HDL-C (mg/dl)				CEC
	Bi-variable model		Multivariable model 1		Bi-variable model		Multivariable model 1
	B (SE)	P value	B (SE)†	P value	B (SE)	P value	B (SE) †	P value
All subjects
ALDH2 ＊1/＊1 genotype	0		0		0		0
ALDH2 ＊1/＊2 or ＊2/＊2 genotype	-5.15 (1.36)	＜0.001	-4.19 (1.24)	0.001	-2.60 (1.27)	0.040	-2.02 (1.26)	0.109
Subjects with no drinking habit
ALDH2 ＊1/＊1 genotype	0		0		0		0
ALDH2 ＊1/＊2 or ＊2/＊2 genotype	-5.96 (2.47)	0.017	-4.82 (2.24)	0.033	-6.00 (2.26)	0.009	-4.75 (2.24)	0.035
Subjects with drinking habit
ALDH2 ＊1/＊1 genotype	0		0		0		0
ALDH2 ＊1/＊2 or ＊2/＊2 genotype	-2.99 (1.78)	0.094	-2.15 (1.64)	0.192	-0.60 (1.67)	0.733	-0.30 (1.68)	0.858

^†Adjusted by age, BMI ≥ 25 kg/m², LDL-C, Log-TGs and smoking status.

ALDH2, aldehyde dehydrogenase 2; HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity; B, unstandardized regression coefficients; SE, standard error; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; TGs, triglycerides.

Associations of Drinking Habits with Levels of HDL-C and CEC

Since we had found that the levels of HDL-C and CEC were lower in carriers of the ALDH2 ^＊2 allele than in those of the ^＊1/^＊1 genotype among non-drinkers only (Table 1, Fig.2, Supplemental Table 1), we next analyzed the influence of drinking habits on the levels of HDL-C and CEC, considering the ALDH2 genotypes and other subject factors. Alcohol consumption was positively correlated with HDL-C levels by Pearson correlation analysis (Fig.3) and multiple regression analysis (Table 2). However, alcohol consumption was not were not correlated with CEC levels (Fig.3 and Table 2). In the analyses stratified by the ALDH2 genotype, alcohol consumption was positively correlated with HDL-C levels but not with CEC levels in both carriers of the ALDH2 ^＊1/^＊1 genotype and the ^＊2 allele (Fig.3 and Table 2).

Fig.3. The correlations of alcohol consumption with the levels of HDL-C and CEC

Pearson correlation analysis. CEC, cholesterol efflux; HDL-C, high-density lipoprotein cholesterol.

Table 2. Associations of levels of HDL-C and CEC with alcohol consumption using regression analysis

	HDL-C (mg/dl)				CEC
	Bi-variable model		Multivariable model 1		Bi-variable model		Multivariable model 1		Multivariable model 2
	B (SE)	P value	B (SE)†	P value	B (SE)	P value	B (SE) †	P value	B (SE)‡	P value
All subjects
Alcohol consumption (g/day)	0.15 (0.04)	＜0.001	0.17 (0.03)	＜0.001	0.02 (0.03)	0.609	0.03 (0.04)	0.396	-0.06 (0.03)	0.063
ALDH2 ＊1/＊1 genotype
Alcohol consumption (g/day)	0.09 (0.05)	0.044	0.15 (0.04)	＜0.001	-0.02 (0.04)	0.701	0.02 (0.04)	0.702	-0.06 (0.04)	0.162
ALDH2 ＊1/＊2 or ＊2/＊2 genotype
Alcohol consumption (g/day)	0.16 (0.06)	0.012	0.20 (0.06)	＜0.001	0.02 (0.06)	0.749	0.05 (0.06)	0.501	-0.07 (0.05)	0.141

^†Adjusted by age, BMI ≥ 25 kg/m², LDL-C, Log-TGs, smoking status and ALDH2 genotype. ^‡Adjusted by HDL-C, age, BMI ≥ 25 kg/m², LDL-C, Log-TGs, smoking status and ALDH2 genotype.

HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity; B, unstandardized regression coefficients; SE, standard error; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; TGs, triglycerides.

We further analyzed associations of drinking habit categories with levels of HDL-C and CEC (Table 3). The levels of HDL-C were higher in subjects with ＜23 g/day, 23-45.9 g/day and ≥ 46 g/day of alcohol consumption than in the non-drinkers in the bi-variable analysis and this association was also observed in multivariable model 1 (Table 3). On the other hand, although no association between drinking habit categories and levels of CEC was observed in the bi-variable model and multivariable model 1 (Table 3), the level of CEC was lower in subjects with ≥ 46 g/day of alcohol consumption than in non-drinkers in multivariable model 2 (Table 3). However, this significant association between CEC levels and drinking habit categories was disappeared after Bonferroni’s correction (Table 3). The trend tests showed that there was significant association of drinking habit categories with HDL-C levels, while there was a tendency in the association with CEC levels (Table 3). Since there is an interactive effect of drinking habit categories and ALDH2 genotype on CEC levels (P=0.021), we performed the stratified analyses by the ALDH2 genotype (Table 3). Higher HDL-C and lower CEC levels were observed in the ALDH2 ^＊1/^＊1 genotype carriers with a drinking habit of ≥ 46 g/day of alcohol consumption than in those with no drinking habit (Table 3). Meanwhile, lower CEC levels were observed in the ALDH2 ^＊2 allele carriers with a drinking habit of ≥ 23 g/day of alcohol consumption than in the ^＊1/^＊1 genotype carriers with no drinking habit (Table 3). However, these significant associations between CEC levels and drinking habit categories in both carriers of the ALDH2 ^＊1/^＊1 genotype and the ^＊2 allele were disappeared after Bonferroni’s correction (Table 3). The trend tests showed that there were significant associations of drinking habit categories with HDL-C levels in both carriers of the ALDH2 ^＊1/^＊1 genotype and the ^＊2 allele (Table 3). In contrast, the trend tests showed that there was no association of drinking habit categories with CEC levels in both carriers of the ALDH2 ^＊1/^＊1 genotype and the ^＊2 allele.

Table 3. Associations of levels of HDL-C and CEC with drinking habit categories using multiple regression analysis

	HDL-C (mg/dl)				CEC
	Bi-variable model		Multivariable model 1		Bi-variable model		Multivariable model 1		Multivariable model 2
	B (SE)	P value	B (SE)†	P value	B (SE)	P value	B (SE)†	P value	B (SE)‡	P value
Drinking habit categories
No drinking habit	0		0	＜0.001§	0		0		0	0.060§
＜23 g/day	4.47 (1.61)	0.006	2.28 (1.50)	0.129	2.80 (1.50)	0.063	1.03 (1.55)	0.506	-0.19 (1.33)	0.889
23-45.9 g/day	5.57 (1.99)	0.005	4.85 (1.90)	0.011	1.52 (1.86)	0.414	1.42 (1.96)	0.468	-1.16 (1.69)	0.493
≥ 46 g/day	8.61 (2.49)	0.001	9.51 (2.34)	＜0.001	0.04 (2.32)	0.987	0.63 (2.41)	0.795	-4.43 (2.10)	0.035||
Combination of the ALDH2 genotype and drinking habit categories
＊1/＊1 & no drinking habit	0		0	§§	0		0		0	§§§
＊1/＊1 & ＜23 g/day	1.69 (2.61)	0.519	1.12 (2.33)	0.632	-1.93 (2.44)	0.428	-2.41 (2.39)	0.315	-3.01 (2.04)	0.142
＊1/＊1 & 23-45.9 g/day	0.94 (2.87)	0.745	2.56 (2.59)	0.324	-1.38 (2.68)	0.606	0.01 (2.66)	0.997	-1.36 (2.27)	0.549
＊1/＊1 & ≥ 46 g/day	5.70 (3.34)	0.089	8.44 (3.01)	0.005	-3.47 (3.12)	0.266	-1.78 (3.09)	0.565	-6.30 (2.66)	0.018||
＊2 allele & no drinking habit	-5.96 (2.65)	0.025||	-4.07 (2.38)	0.089	-6.00 (2.47)	0.015||	-4.79 (2.45)	0.051	-2.61 (2.10)	0.213
＊2 allele & ＜23 g/day	-2.00 (2.80)	0.474	-1.39 (2.52)	0.582	-0.76 (2.60)	0.769	-0.92 (2.59)	0.722	-0.18 (2.21)	0.937
＊2 allele & 23-45.9 g/day	2.61 (3.93)	0.507	4.59 (3.54)	0.196	-7.10 (3.66)	0.053	-5.11 (3.64)	0.161	-7.57 (3.11)	0.015||
＊2 allele & ≥ 46 g/day	0.28 (4.91)	0.955	5.30 (4.50)	0.239	-6.57 (4.57)	0.151	-2.76 (4.61)	0.550	-5.60 (3.95)	0.156

^†Adjusted by age, BMI ≥ 25 kg/m², LDL-C, Log-TGs, smoking status and ALDH2 genotype. ^‡Adjusted by HDL-C age, BMI ≥ 25 kg/m², LDL-C, Log-TGs, smoking status and ALDH2 genotype. ^§P values for trend. ^§§P values for trend in HDL-C levels with drinking habit categories among the carriers of ALDH2 ^＊1/^＊1 genotype and those of ^＊2 allele were 0.010 and 0.002, respectively. ^§§§P values for trend in CEC levels with drinking habit categories among the carriers of ALDH2 ^＊1/^＊1 genotype and those of ^＊2 allele were 0.134 and 0.086,

respectively. ^|| Significance disappeared after Bonferroni’s correction.

HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity; B, unstandardized regression coefficients; SE, standard error; ALDH2, aldehyde dehydrogenase; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; TGs, triglycerides.

Since we had found that the ALDH2 genotype was tended to be associated with the association of drinking habit categories with HDL-C and CEC levels (Table 3), we next analyzed an association of ALDH2 genotype with antioxidant and oxidative stress markers (Supplemental Table 2). Carriers of the ALDH2 ^＊1/^＊2 or ^＊2/^＊2 genotype had lower albumin and UA levels and tended to be higher oxidized HSA levels compared to carriers of the ^＊1/^＊1 genotype (Supplemental Table 2). Among drinkers, the level of albumin was lower and that of oxidized HSA was higher in carriers of the ALDH2 ^＊1/^＊2 or ^＊2/^＊2 genotype than in those of the ^＊1/^＊1 genotype (Supplemental Table 2). In contrast, among the non-drinkers, no association of ALDH2 genotypes with antioxidant and oxidative stress markers was observed (Supplemental Table 2).

Supplemental Table 2. Associations of ALDH2 rs671 polymorphism with antioxidant or oxidative stress markers

	Albumin (g/dL)		UA (mg/dL)		Total bilirubin (mg/dL)		Oxidized HSA (%)
	B (SE)†	P value	B (SE) †	P value	B (SE) †	P value	B (SE) †	P value
All subjects
ALDH2 ＊1/＊1 genotype	0		0		0		0
ALDH2 ＊1/＊2 or ＊2/＊2 genotype	-0.04 (0.02)	0.043	-0.38 (0.11)	0.001	-0.04 (0.03)	0.170	0.60 (0.34)	0.076
Subjects with no drinking habit
ALDH2 ＊1/＊1 genotype	0		0		0		0
ALDH2 ＊1/＊2 or ＊2/＊2 genotype	0.03 (0.04)	0.467	-0.33 (0.22)	0.138	0.01 (0.06)	0.855	-0.45 (0.82)	0.587
Subjects with drinking habit
ALDH2 ＊1/＊1 genotype	0		0		0		0
ALDH2 ＊1/＊2 or ＊2/＊2 genotype	-0.08 (0.03)	0.003	-0.23 (0.14)	0.096	-0.05 (0.04)	0.241	0.75 (0.38)	0.048

^†Adjusted by age, BMI ≥ 25 kg/m², LDL, log TG, smoking status and HDL-C.

ALDH2, aldehyde dehydrogenase 2; UA, uric acid; HSA, human serum albumin; B, unstandardized regression coefficients; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; TGs, triglycerides; HDL-C, high-density lipoprotein cholesterol.

It has been reported that weight status is associated with the level of CEC¹⁰⁾, and in the present study, the levels of HDL-C and CEC were lower in overweight subjects than in normal-weight subjects (Supplemental Fig.2). Therefore, we assessed the associations of drinking habits with levels of CEC and HDL-C stratified by weight status (Supplemental Table 3). The trend tests showed that there were significant associations of drinking habit categories with HDL-C level among both overweight and normal-weight subjects (Supplemental Table 3). Moreover, the multivariable model showed that the level of HDL-C was higher in subjects with ＜23 g/day, 23-45.9 g/day or ≥ 46 g/day of alcohol consumption than in those with no drinking habit among both overweight and normal-weight subjects (Supplemental Table 3). On the other hand, the trend tests showed that there was a significant association between CEC level and drinking habit categories among only normal-weight subjects (Supplemental Table 3). Moreover, the multivariable model also showed that the levels of CEC were lower in subjects with alcohol consumption of ≥ 46 g/day than in those with no drinking habit only among normal-weight subject, but this significant association was disappeared after Bonferroni’s correction (Supplemental Table 3).

Supplementary Fig.2. The association of weight status with levels of HDL-C and CEC

Data shown are mean±SE. P values were calculated by Student’s t-test. HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity; SE, standarderror.

Supplemental Table 3. Associations of levels of CEC and HDL-C with drinking habit categories among normal weight or overweight subjects

	HDL-C (mg/dl)				CEC
	Bi-variable model		Multivariable model		Bi-variable model		Multivariable model 1		Multivariable model 2
	B (SE)	P value	B (SE) †	P value	B (SE)	P value	B (SE)†	P value	B (SE)‡	P value
Subjects with normal weight
No drinking habit	0		0	0.003§	0		0		0	0.034§
0.1-22.9 g/day	2.51 (1.89)	0.186	1.43 (1.76)	0.415	2.15 (1.73)	0.215	0.94 (1.78)	0.600	0.21 (1.55)	0.893
23-45.9 g/day	3.35 (2.37)	0.156	3.70 (2.33)	0.113	-0.99 (2.17)	0.648	-0.65 (2.36)	0.784	-2.53 (2.05)	0.220
＞46 g/day	6.60 (2.97)	0.027	8.97 (2.86)	＜0.001	-1.35 (2.72)	0.619	-0.83 (2.90)	0.775	-5.39 (2.55)	0.035||
Overweight subjects
No drinking habit	0		0	0.003§	0		0		0	0.545§
0.1-22.9 g/day	6.84 (2.91)	0.020	4.87 (2.94)	0.101	2.83 (2.97)	0.342	0.92 (3.15)	0.769	-2.01 (2.64)	0.449
23-45.9 g/day	9.77 (3.45)	0.005	7.64 (3.44)	0.028||	6.96 (3.52)	0.050	5.17 (3.68)	0.163	0.57 (3.11)	0.854
＞46 g/day	12.48 (4.26)	0.004	11.42 (4.17)	0.007	2.84 (4.34)	0.515	2.90 (4.46)	0.518	-3.98 (3.81)	0.298

^†Adjusted by age, BMI ≥ 25 kg/m², LDL-C, Log-TGs, smoking status and ALDH2 genotype.

^‡Adjusted by HDL-C, age, BMI ≥ 25 kg/m², LDL-C, Log-TGs, smoking status and ALDH2 genotype.

^§P values for trend.

^|| Significance disappeared after Bonferroni’s correction.

HDL-C, high-density lipoprotein cholesterol; CEC, cholesterol efflux capacity; B, unstandardized regression coefficients; SE, standard error; BMI, body mass index; LDL-C, low-density lipoprotein cholesterol; TGs, triglycerides; ALDH2, aldehyde dehydrogenase 2.

Discussion

This is the first study to show that a heavier drinking habit (more than 46 g/day of alcohol consumption) tend to be associated with a decreased level of CEC despite an increase in HDL-C level. Therefore, high HDL-C levels in heavy drinkers do not necessarily mean that CEC is also high. Moreover, CEC levels were lower in carriers of the ALDH2 ^＊2 allele than in those of the ^＊1/^＊1 genotype, and the decreasing effect of drinking habit on CEC levels tended to be pronounced in carriers of the ^＊2 allele. This indicates that the amount of CEC may be affected not only by intake of alcohol but also a susceptible genetic background. Additionally, our data suggest that drinking should not be recommended to drinkers with low alcohol tolerance to increase HDL-C levels.

In the present study, the bi-variable analyses showed that drinking habits were associated with increased HDL-C levels, but not CEC levels (Table 2-3). Interestingly, the multivariable analyses adjusted for confounding factors including HDL-C showed that alcohol consumption of ＞46 g/day tended to be associated with decreased CEC levels (Table 3). Based on these results, we suggest that a heavy drinking habit increases HDL-C levels but may decrease CEC per unit of HDL-C. HDL particles are divided into subclasses by size, density, charge, and composition. The lower molecular weight, higher density and relatively cholesterol-poor form is classified as HDL₃, and the higher molecular weight, lower density and relatively cholesterol-rich form as HDL₂ ³⁷⁾. HDL₃ is the major HDL subclass involved in cholesterol efflux from peripheral cells³⁸⁾, and sphingosine-1-phosphate and its carrier protein, APOM, contained in HDL₃ are directly associated with CEC³⁹⁾. On the other hand, several enzymes are involved in HDL metabolism and remodeling, phospholipid transfer protein (PLTP) appears to convert HDL₃ into HDL₂, and CETP promotes the formation of small HDL⁴⁰⁾. It has been reported that alcohol intake increases HDL₂ levels primarily through a decrease in CETP activity and an increase in PLTP activity^{40, 41)}. Therefore, alcohol intake is associated with an increase in HDL-C levels by increasing HDL₂ through increased PLTP activity, but, conversely, an increase in PLTP activity may lead to a decrease in HDL₃, resulting in reduced CEC for HDL-C.

It has also been reported that the vasodilatory activity of HDL is inversely correlated with its TG content⁴²⁾. Alcohol intake (i.e., ethanol exposure) increases hepatic uptake of exogenous fatty acids (FAs) and subsequent incorporation of FAs (e.g., palmitate) into TGs in the liver, thereby increasing the release of TGs in the form of VLDL-loaded into the blood^{13, 43)}. Elevated blood levels of TGs cause the formation of TG-rich and cholesterol-ester-depleted HDL particles that are rapidly removed from the circulation, primarily by uptake into the liver, some of which are converted to HDL₃ by hepatic triglyceride lipase (HTGL)⁴⁴⁾. In addition, HDL₂ has been reported to be inversely correlated with HTGL activity⁴⁵⁾, so an increase in HDL₂ level due to alcohol intake may be associated with a decrease in HTGL activity. Therefore, a heavy drinking habit may increase TG-rich HDL particles, which have lower cholesterol efflux capacity, by promoting TG synthesis and/or inhibiting the conversion of TG-rich HDL to HDL₃, resulting in decreased CEC levels.

A previous epidemiological study has shown that HDL-C levels were lower in carriers of the ALDH2 ^＊2 allele than in carriers of the ^＊1/^＊1 genotype²⁴⁾, and a similar association was observed even in subjects with no drinking habit²⁷⁾. In the present study, both levels of HDL-C and CEC were lower in carriers of the ALDH2 ^＊2 allele than in those of the ^＊1/^＊1 genotype among all subjects and non-drinkers (Fig.2 and Supplemental Table 1). ALDH2 detoxifies not only acetaldehyde derived from alcohol but also other reactive aldehydic products including malondialdehyde (MDA), methylglyoxal and 4-hydroxynonenal, which induce protein carbonylation and mitochondrial dysfunction²¹⁾. A previous in vitro study showed that MDA impaired CEC for HDL by modification of apolipoprotein (APO) A-I, a major protein component of HDL particles⁴⁶⁾. Therefore, ALDH2 dysfunction derived from the ALDH2 rs671 polymorphism can accelerate the accumulation of reactive aldehydes, leading to a decrease in CEC for HDL.

In the multiple regression analyses with adjustment for HDL-C level, the association between alcohol intake and a decrease in CEC levels tended to be more pronounced in the ALDH2 ^＊2 allele carriers than in the 1/^＊ 1 genotype carriers (Table 3). Among the ALDH2 ^＊2 allele carriers, CEC levels tended to be lower in subjects with an alcohol consumption of 23-45.9 g/day compared to those with no drinking habit, whereas CEC levels tended to be lower in subjects with a greater amount of alcohol consumption, i.e., ＞46 g/day, compared to those with no drinking habit among the ^＊1/^＊1 genotype carriers (Table 3). Furthermore, among the drinkers, levels of albumin were lower and those of oxidized HSA were higher in carriers of the ALDH2 ^＊2 allele than in those of the ^＊1/^＊1 genotype, suggesting that ^＊2 allele carriers are more likely to be exposed to oxidative stress derived from alcohol consumption (Supplemental Table 2). Therefore, ALDH2 ^＊2 allele carriers may be more susceptible to a decrease in CEC caused by alcohol intake, even if the amount of alcohol is low, as compared with the ^＊1/^＊1 genotype, due to low detoxification capacity for ethanol-derived acetaldehyde.

Alcohol consumption is associated with several individual factors (e.g., cigarette smoking, obesity, sex), which may also be associated with lower CEC levels¹⁰⁾. Cigarette smoking has been reported to reduce CEC as well as HDL-C, and smokers have been shown to have reduced ABCA1-mediated cholesterol efflux compared with non-smokers¹⁰⁾. The multivariable analyses adjusted for HDL-C levels indicated that drinking habits were associated with decreased levels of CEC independently of smoking status (Table 3). Therefore, we suggest that acetaldehydes derived from alcohol intake may be associated with a decrease in CEC for HDL particles regardless of smoking habits. Increased BMI was reported to be associated with decreased APOA-I and HDL-C levels¹⁰⁾, and obesity to be associated with reduced CEC levels due to a decrease in genes related to cholesterol metabolism (e.g., ABCA1, ABCG1)¹⁰⁾. In our analysis stratified by weight status, an association between drinking habits and CEC levels was observed in the normal weight subjects, but not in the overweight subjects (Supplemental Table 3). Since CEC levels in overweight subjects were lower than normal-weight subjects (Supplemental Fig.2), there may be loss of the effects of alcohol consumption on CEC levels in overweight subjects. Furthermore, a previous study showed that both HDL-C and CEC levels were higher in pre-menopausal female subjects than in male subjects⁴⁷⁾, but the impact of menopause on CEC levels is not well understood¹⁰⁾. Since the present study was conducted in male subjects only, further studies in female subjects are needed to investigate the association between drinking habits and CEC levels, including the effects of menopause.

In the current study, we found that drinking habits tended to be associated with lower CEC levels, independently of HDL-C levels (Table 3). In contrast, a previous cross-sectional study conducted in 1,932 Caucasians showed that alcohol consumption was associated with increased CEC levels, without any relation to HDL-C levels¹⁶⁾. Moreover, a previous cross-over trial with a 4-week intervention period showed that moderate beer consumption (30 g for men and 15 g for women in terms of ethanol) increased CEC levels¹⁷⁾. Another cross-sectional study found no association between drinking habits and CEC levels¹⁸⁾. We speculate that the differences in the results among the present study and these previous studies may result from differences in races and genetic polymorphisms. It is well-known that the frequency of ALDH2 ^＊2 allele varies among races, with ^＊2 allele carriers common among East Asians but not other racial groups, and thus, racial differences may also be important in associations between drinking habits and CEC levels. In addition, differences in genotypes other than the ALDH2 genotype might also affect CEC levels^{22, 48)}. The frequency of ADH1B rs1229984 polymorphisms associated with reduced ability to convert alcohol to acetaldehyde differs between races²²⁾, and they are more common in Caucasians than in East Asians²²⁾. Furthermore, a recent genome-wide association study has identified genetic variations at the APOE/C1/C2/C4 locus associated with CEC levels independent of HDL-C levels⁴⁸⁾. Although further studies on diverse populations incorporating several genotypes are needed, simultaneous measurement of CEC levels and the ALDH2 rs671 genotype may contribute to appropriate lifestyle modification (e.g., moderation in alcohol intake) and precision/personalized medicine.

Several limitations of the present study should be noted. APOA-I is a small sized particle in HDL and has been reported to be more closely related to CEC levels than HDL-C levels^{49, 50)}. Therefore, it is important to examine the relationship between drinking habits, APOA-1 and CEC levels in order to clarify the effects of drinking habits on CEC levels, but we were unable to measure APOA1 levels in our study. Further studies are needed to comprehensively examine the relationship between drinking habits, ALDH2 genotype, APO-AI and CEC levels. Information regarding the subjects’ alcohol consumption and smoking status may have lacked reliability because it was evaluated through face-to-face interviews (e.g., there might have been bias related to under-evaluation of alcohol consumption). Moreover, there is the possibility that the association between drinking habits and CEC levels may be influenced by not only current drinking habits but also past drinking habits, but we could not collect information on past drinking habits. Furthermore, the present study has a retrospective cross-sectional design, and the number of subjects was small. Although the statistical power of this study were above the required power limit (i.e., 80%), alcohol consumption and drinking habit categories did not reach the statistically significant effects on CEC levels, because the actual effect size was smaller than the estimated effect size. Further investigations in larger populations and/or according to a prospective design are needed to verify our findings.

Conclusion

A heavy drinking habit is associated with quantitative increases in HDL-C levels but may tend to decrease CEC for HDL particles. Additionally, the decreasing tendency effect of drinking habits on CEC for HDL particles may be more pronounced in carriers of the ALDH2^＊2 allele than in those of the ^＊1/^＊1 genotype. In the future, simultaneous measurement of both CEC levels and the ALDH2 rs671 polymorphism may be useful for lifestyle modification, such as moderation in alcohol intake, as well as precision/personalized medicine.

Acknowledgments and Notice of Grants Support

We are grateful to Ms. Megumu Horiuchi (Department of Molecular Innovation in Lipidology, National Cerebral and Cardiovascular Center Research Institute) for her technical assistance. This work was supported by grants from JSPS KAKENHI (Grant Numbers: JP18K08125, 19K07166 and 20K07134) and by a grant from Smoking Research Foundation, Ono Medical Research Foundation, and SENSHIN Medical Research Foundation. None of the funders played a role in the design, implementation, analysis, and interpretation of the data.

References

• 1)  Ko DT, Alter DA, Guo H, Koh M, Lau G, Austin PC, Booth GL, Hogg W, Jackevicius CA, Lee DS, Wijeysundera HC, Wilkins JT and Tu JV: High-Density Lipoprotein Cholesterol and Cause-Specific Mortality in Individuals Without Previous Cardiovascular Conditions: The CANHEART Study. J Am Coll Cardiol, 2016; 68: 2073-2083
• 2)  Madsen CM, Varbo A and Nordestgaard BG: Extreme high high-density lipoprotein cholesterol is paradoxically associated with high mortality in men and women: two prospective cohort studies. Eur Heart J, 2017; 38: 2478-2486
• 3)  Hirata A, Sugiyama D, Watanabe M, Tamakoshi A, Iso H, Kotani K, Kiyama M, Yamada M, Ishikawa S, Murakami Y, Miura K, Ueshima H, Okamura T and Evidence for Cardiovascular Prevention from Observational Cohorts in Japan Research G: Association of extremely high levels of high-density lipoprotein cholesterol with cardiovascular mortality in a pooled analysis of 9 cohort studies including 43,407 individuals: The EPOCH-JAPAN study. J Clin Lipidol, 2018; 12: 674-684 e675
• 4)  Keene D, Price C, Shun-Shin MJ and Francis DP: Effect on cardiovascular risk of high density lipoprotein targeted drug treatments niacin, fibrates, and CETP inhibitors: meta-analysis of randomised controlled trials including 117,411 patients. BMJ, 2014; 349: g4379
• 5)  Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, Hindy G, Holm H, Ding EL, Johnson T, Schunkert H, Samani NJ, Clarke R, Hopewell JC, Thompson JF, Li M, Thorleifsson G, Newton-Cheh C, Musunuru K, Pirruccello JP, Saleheen D, Chen L, Stewart A, Schillert A, Thorsteinsdottir U, Thorgeirsson G, Anand S, Engert JC, Morgan T, Spertus J, Stoll M, Berger K, Martinelli N, Girelli D, McKeown PP, Patterson CC, Epstein SE, Devaney J, Burnett MS, Mooser V, Ripatti S, Surakka I, Nieminen MS, Sinisalo J, Lokki ML, Perola M, Havulinna A, de Faire U, Gigante B, Ingelsson E, Zeller T, Wild P, de Bakker PI, Klungel OH, Maitland-van der Zee AH, Peters BJ, de Boer A, Grobbee DE, Kamphuisen PW, Deneer VH, Elbers CC, Onland-Moret NC, Hofker MH, Wijmenga C, Verschuren WM, Boer JM, van der Schouw YT, Rasheed A, Frossard P, Demissie S, Willer C, Do R, Ordovas JM, Abecasis GR, Boehnke M, Mohlke KL, Daly MJ, Guiducci C, Burtt NP, Surti A, Gonzalez E, Purcell S, Gabriel S, Marrugat J, Peden J, Erdmann J, Diemert P, Willenborg C, Konig IR, Fischer M, Hengstenberg C, Ziegler A, Buysschaert I, Lambrechts D, Van de Werf F, Fox KA, El Mokhtari NE, Rubin D, Schrezenmeir J, Schreiber S, Schafer A, Danesh J, Blankenberg S, Roberts R, McPherson R, Watkins H, Hall AS, Overvad K, Rimm E, Boerwinkle E, Tybjaerg-Hansen A, Cupples LA, Reilly MP, Melander O, Mannucci PM, Ardissino D, Siscovick D, Elosua R, Stefansson K, O’Donnell CJ, Salomaa V, Rader DJ, Peltonen L, Schwartz SM, Altshuler D and Kathiresan S: Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet, 2012; 380: 572-580
• 6)  Rhainds D and Tardif JC: From HDL-cholesterol to HDL-function: cholesterol efflux capacity determinants. Curr Opin Lipidol, 2019; 30: 101-107
• 7)  Rohatgi A, Khera A, Berry JD, Givens EG, Ayers CR, Wedin KE, Neeland IJ, Yuhanna IS, Rader DR, de Lemos JA and Shaul PW: HDL cholesterol efflux capacity and incident cardiovascular events. N Engl J Med, 2014; 371: 2383-2393
• 8)  Nakamura M, Yamamoto Y, Imaoka W, Kuroshima T, Toragai R, Ito Y, Kanda E, E JS and Ai M: Relationships between Smoking Status, Cardiovascular Risk Factors, and Lipoproteins in a Large Japanese Population. J Atheroscler Thromb, 2021; 28: 942-953
• 9)  Komatsu T and Uehara Y: High-Density Lipoprotein Cholesterol Efflux Capacity as a Surrogate Marker for Major Cardiac Adverse Events in Japanese Patients. J Atheroscler Thromb, 2021; 28: 692-693
• 10)  Talbot CPJ, Plat J, Ritsch A and Mensink RP: Determinants of cholesterol efflux capacity in humans. Prog Lipid Res, 2018; 69: 21-32
• 11)  Langer RD, Criqui MH and Reed DM: Lipoproteins and blood pressure as biological pathways for effect of moderate alcohol consumption on coronary heart disease. Circulation, 1992; 85: 910-915
• 12)  Mukamal KJ, Jensen MK, Gronbaek M, Stampfer MJ, Manson JE, Pischon T and Rimm EB: Drinking frequency, mediating biomarkers, and risk of myocardial infarction in women and men. Circulation, 2005; 112: 1406-1413
• 13)  Huang S, Li J, Shearer GC, Lichtenstein AH, Zheng X, Wu Y, Jin C, Wu S and Gao X: Longitudinal study of alcohol consumption and HDL concentrations: a community-based study. Am J Clin Nutr, 2017; 105: 905-912
• 14)  Avdulov NA, Chochina SV, Igbavboa U and Wood WG: Cholesterol efflux to high-density lipoproteins and apolipoprotein A-I phosphatidylcholine complexes is inhibited by ethanol: role of apolipoprotein structure and cooperative interaction of phosphatidylcholine and cholesterol. Biochemistry, 2000; 39: 10599-10606
• 15)  Marmillot P, Munoz J, Patel S, Garige M, Rosse RB and Lakshman MR: Long-term ethanol consumption impairs reverse cholesterol transport function of high-density lipoproteins by depleting high-density lipoprotein sphingomyelin both in rats and in humans. Metabolism, 2007; 56: 947-953
• 16)  Koekemoer AL, Codd V, Masca NGD, Nelson CP, Musameh MD, Kaess BM, Hengstenberg C, Rader DJ and Samani NJ: Large-Scale Analysis of Determinants, Stability, and Heritability of High-Density Lipoprotein Cholesterol Efflux Capacity. Arterioscler Thromb Vasc Biol, 2017; 37: 1956-1962
• 17)  Padro T, Munoz-Garcia N, Vilahur G, Chagas P, Deya A, Antonijoan RM and Badimon L: Moderate Beer Intake and Cardiovascular Health in Overweight Individuals. Nutrients, 2018; 10: 1237
• 18)  Perret B, Ruidavets JB, Vieu C, Jaspard B, Cambou JP, Terce F and Collet X: Alcohol consumption is associated with enrichment of high-density lipoprotein particles in polyunsaturated lipids and increased cholesterol esterification rate. Alcohol Clin Exp Res, 2002; 26: 1134-1140
• 19)  Erol A and Karpyak VM: Sex and gender-related differences in alcohol use and its consequences: Contemporary knowledge and future research considerations. Drug Alcohol Depend, 2015; 156: 1-13
• 20)  Ferreira MP and Weems MK: Alcohol consumption by aging adults in the United States: health benefits and detriments. J Am Diet Assoc, 2008; 108: 1668-1676
• 21)  Chen CH, Ferreira JC, Gross ER and Mochly-Rosen D: Targeting aldehyde dehydrogenase 2: new therapeutic opportunities. Physiol Rev, 2014; 94: 1-34
• 22)  Edenberg HJ: The genetics of alcohol metabolism: role of alcohol dehydrogenase and aldehyde dehydrogenase variants. Alcohol Res Health, 2007; 30: 5-13
• 23)  Mizoi Y, Yamamoto K, Ueno Y, Fukunaga T and Harada S: Involvement of genetic polymorphism of alcohol and aldehyde dehydrogenases in individual variation of alcohol metabolism. Alcohol Alcohol, 1994; 29: 707-710
• 24)  Kato N, Takeuchi F, Tabara Y, Kelly TN, Go MJ, Sim X, Tay WT, Chen CH, Zhang Y, Yamamoto K, Katsuya T, Yokota M, Kim YJ, Ong RT, Nabika T, Gu D, Chang LC, Kokubo Y, Huang W, Ohnaka K, Yamori Y, Nakashima E, Jaquish CE, Lee JY, Seielstad M, Isono M, Hixson JE, Chen YT, Miki T, Zhou X, Sugiyama T, Jeon JP, Liu JJ, Takayanagi R, Kim SS, Aung T, Sung YJ, Zhang X, Wong TY, Han BG, Kobayashi S, Ogihara T, Zhu D, Iwai N, Wu JY, Teo YY, Tai ES, Cho YS and He J: Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians. Nat Genet, 2011; 43: 531-538
• 25)  Mizuno Y, Hokimoto S, Harada E, Kinoshita K, Nakagawa K, Yoshimura M, Ogawa H and Yasue H: Variant Aldehyde Dehydrogenase 2 (ALDH2^＊2) Is a Risk Factor for Coronary Spasm and ST-Segment Elevation Myocardial Infarction. J Am Heart Assoc, 2016; 5:
• 26)  Morita K, Saruwatari J, Miyagawa H, Uchiyashiki Y, Oniki K, Sakata M, Kajiwara A, Yoshida A, Jinnouchi H and Nakagawa K: Association between aldehyde dehydrogenase 2 polymorphisms and the incidence of diabetic retinopathy among Japanese subjects with type 2 diabetes mellitus. Cardiovasc Diabetol, 2013; 12: 132
• 27)  Wada M, Daimon M, Emi M, Iijima H, Sato H, Koyano S, Tajima K, Kawanami T, Kurita K, Hunt SC, Hopkins PN, Kubota I, Kawata S and Kato T: Genetic association between aldehyde dehydrogenase 2 (ALDH2) variation and high-density lipoprotein cholesterol (HDL-C) among non-drinkers in two large population samples in Japan. J Atheroscler Thromb, 2008; 15: 179-184
• 28)  Sakamoto Y, Oniki K, Kumagae N, Morita K, Otake K, Ogata Y and Saruwatari J: Beta-3-adrenergic Receptor rs4994 Polymorphism Is a Potential Biomarker for the Development of Nonalcoholic Fatty Liver Disease in Overweight/Obese Individuals. Dis Markers, 2019; 2019: 4065327
• 29)  Lin Y, Kikuchi S, Tamakoshi A, Wakai K, Kawamura T, Iso H, Ogimoto I, Yagyu K, Obata Y, Ishibashi T and Group JS: Alcohol consumption and mortality among middle-aged and elderly Japanese men and women. Ann Epidemiol, 2005; 15: 590-597
• 30)  WHO expert consulutation. 1995;
• 31)  Ogura M, Hori M and Harada-Shiba M: Association Between Cholesterol Efflux Capacity and Atherosclerotic Cardiovascular Disease in Patients With Familial Hypercholesterolemia. Arterioscler Thromb Vasc Biol, 2016; 36: 181-188
• 32)  Furuhashi M, Ogura M, Matsumoto M, Yuda S, Muranaka A, Kawamukai M, Omori A, Tanaka M, Moniwa N, Ohnishi H, Saitoh S, Harada-Shiba M, Shimamoto K and Miura T: Serum FABP5 concentration is a potential biomarker for residual risk of atherosclerosis in relation to cholesterol efflux from macrophages. Sci Rep, 2017; 7: 217
• 33)  Imafuku T, Watanabe H, Oniki K, Yoshida A, Kato H, Nakano T, Tokumaru K, Fujita I, Arimura N, Maeda H, Sakamoto Y, Kondo N, Morita A, Saruwatari J, Tanaka M, Matsushita K, Wada T, Fukagawa M, Otagiri M, Fitzgerald ML, Jinnouchi H and Maruyama T: Cysteinylated Albumin as a Potential Biomarker for the Progression of Kidney Disease in Patients With Type 2 Diabetes. Diabetes Care, 2021;
• 34)  Watanabe H, Imafuku T, Otagiri M and Maruyama T: Clinical Implications Associated With the Posttranslational Modification-Induced Functional Impairment of Albumin in Oxidative Stress-Related Diseases. J Pharm Sci, 2017; 106: 2195-2203
• 35)  Hayashi T, Suda K, Imai H and Era S: Simple and sensitive high-performance liquid chromatographic method for the investigation of dynamic changes in the redox state of rat serum albumin. J Chromatogr B Analyt Technol Biomed Life Sci, 2002; 772: 139-146
• 36)  Higuchi S, Matsushita S, Muramatsu T, Murayama M and Hayashida M: Alcohol and aldehyde dehydrogenase genotypes and drinking behavior in Japanese. Alcohol Clin Exp Res, 1996; 20: 493-497
• 37)  Kontush A, Lhomme M and Chapman MJ: Unraveling the complexities of the HDL lipidome. Journal of lipid research, 2013; 54: 2950-2963
• 38)  Du XM, Kim MJ, Hou L, Le Goff W, Chapman MJ, Van Eck M, Curtiss LK, Burnett JR, Cartland SP, Quinn CM, Kockx M, Kontush A, Rye KA, Kritharides L and Jessup W: HDL particle size is a critical determinant of ABCA1-mediated macrophage cellular cholesterol export. Circ Res, 2015; 116: 1133-1142
• 39)  Badimon L, Padro T and Cubedo J: Protein changes in non-LDL-lipoproteins in familial hypercholesterolemia: implications in cardiovascular disease manifestation and outcome. Curr Opin Lipidol, 2017; 28: 427-433
• 40)  Niesor EJ: Different effects of compounds decreasing cholesteryl ester transfer protein activity on lipoprotein metabolism. Curr Opin Lipidol, 2011; 22: 288-295
• 41)  Makela SM, Jauhiainen M, Ala-Korpela M, Metso J, Lehto TM, Savolainen MJ and Hannuksela ML: HDL2 of heavy alcohol drinkers enhances cholesterol efflux from raw macrophages via phospholipid-rich HDL 2b particles. Alcohol Clin Exp Res, 2008; 32: 991-1000
• 42)  Persegol L, Verges B, Foissac M, Gambert P and Duvillard L: Inability of HDL from type 2 diabetic patients to counteract the inhibitory effect of oxidised LDL on endothelium-dependent vasorelaxation. Diabetologia, 2006; 49: 1380-1386
• 43)  You M and Arteel GE: Effect of ethanol on lipid metabolism. J Hepatol, 2019; 70: 237-248
• 44)  Rashid S, Barrett PH, Uffelman KD, Watanabe T, Adeli K and Lewis GF: Lipolytically modified triglyceride-enriched HDLs are rapidly cleared from the circulation. Arterioscler Thromb Vasc Biol, 2002; 22: 483-487
• 45)  Applebaum-Bowden D, Haffner SM, Wahl PW, Hoover JJ, Warnick GR, Albers JJ and Hazzard WR: Postheparin plasma triglyceride lipases. Relationships with very low density lipoprotein triglyceride and high density lipoprotein2 cholesterol. Arteriosclerosis, 1985; 5: 273-282
• 46)  Shao B, Pennathur S, Pagani I, Oda MN, Witztum JL, Oram JF and Heinecke JW: Modifying apolipoprotein A-I by malondialdehyde, but not by an array of other reactive carbonyls, blocks cholesterol efflux by the ABCA1 pathway. J Biol Chem, 2010; 285: 18473-18484
• 47)  Catalano G, Duchene E, Julia Z, Le Goff W, Bruckert E, Chapman MJ and Guerin M: Cellular SR-BI and ABCA1-mediated cholesterol efflux are gender-specific in healthy subjects. Journal of lipid research, 2008; 49: 635-643
• 48)  Low-Kam C, Rhainds D, Lo KS, Barhdadi A, Boule M, Alem S, Pedneault-Gagnon V, Rheaume E, Dube MP, Busseuil D, Hegele RA, Lettre G and Tardif JC: Variants at the APOE /C1/C2/C4 Locus Modulate Cholesterol Efflux Capacity Independently of High-Density Lipoprotein Cholesterol. J Am Heart Assoc, 2018; 7: e009545
• 49)  Asztalos BF, Horvath KV, Mehan M, Yokota Y and Schaefer EJ: Influence of HDL particles on cell-cholesterol efflux under various pathological conditions. Journal of lipid research, 2017; 58: 1238-1246
• 50)  Thakkar H, Vincent V, Roy A, Singh S, Ramakrishnan L, Kalaivani M and Singh A: HDL functions and their interaction in patients with ST elevation myocardial infarction: a case control study. Lipids Health Dis, 2020; 19: 75