Alcohol Consumption and Cerebral Small- and Large-Vessel Diseases: A Mendelian Randomization Analysis

Abstract

Aims: It remains inconclusive regarding alcohol intake and stroke risk because determining risk factors depends on the specific pathogenesis of stroke. We used the variant rs671 in the aldehyde dehydrogenase 2 gene (ALDH2) as an instrument to investigate the causal role of alcohol intake in cerebral small- and large-vessel diseases.

Methods: We studied 682 men (mean age, 70.0 years), without stroke, in a cross-sectional Mendelian randomization analysis. We assessed small-vessel diseases (SVDs), which comprised lacunar infarcts, white matter hyperintensities (WMHs), and cerebral microbleeds, and large intracranial artery stenosis (ICAS) on brain magnetic resonance imaging.

Results: The median (25%tiles, 75%tiles) alcohol consumption by ALDH2-rs671 inactive A allele (n=313 [45.9%]) and non-A allele (n=369 [54.1%]) carriers was 3.5 (0.0, 16.0) and 32.0 (12.9, 50.0) g/day, respectively. Non-A allele carriers had higher prevalent hypertension and lower low-density lipoprotein cholesterol concentrations than A allele carriers. In age-adjusted ordinal logistic regression for graded burden, odds ratios (95% confidence intervals) for total SVDs, lacunar infarcts, WMHs, cerebral microbleeds, and ICAS in non-Aallele carriers were 1.46 (1.09-1.94), 1.41 (0.95-2.08), 1.39 (1.05-1.85), 1.69 (1.06-2.69), and 0.70 (0.50-0.98), respectively, compared with A allele carriers. These associations attenuated to statistical non-significance after considering covariates and amount of alcohol intake.

Conclusions: Our findings suggest a positive association of alcohol consumption with risk of cerebral SVDs and its inverse association with risk of large-vessel disease through intermediaries, such as hypertension or low-density lipoprotein cholesterol. These findings provide insight into potential causal mechanisms linking alcohol consumption with stroke risk.

See editorial vol. 31: 119-121

Introduction

Observational studies have shown that light to moderate alcohol consumption is associated with a reduced risk of cardiovascular disease compared with no alcohol consumption^1-3). However, this apparently protective association does not necessarily indicate that alcohol intake itself is protective against cardiovascular disease. Underlying poor health might affect alcohol consumption, especially in non-drinkers (reverse causality), and there might be other systematic differences among people with different drinking patterns that are not taken into account (residual confounding)^{4, 5)}. In the absence of available randomized trial to confirm or refute the effect of alcohol consumption on cardiovascular disease, an alternative approach is to use a genetic variant that serves as a proxy for alcohol consumption. This approach, known as Mendelian randomization, avoids some of the main limitations of observational studies because allocation of genetic variants is random with regard to potential confounders (thus removing residual confounding), and the genotype is not modified by disease (thus abolishing reverse causality)^{6, 7)}.

The single-nucleotide polymorphism (SNP) rs671 in the aldehyde dehydrogenase 2 gene (ALDH2), which encodes the ALDH2 enzyme, provides the primary pathway of alcohol metabolism. The ALDH2-rs671 variant, which is common only in East Asian populations, greatly slows acetaldehyde breakdown, and the resulting accumulation of acetaldehyde can cause severe discomfort that strongly reduces alcohol consumption. This can lead to selection of the SNP rs671 as a genetic instrument in Mendelian randomization analysis. The effects of genetic findings of the ALDH2-rs671 variant on cardiovascular risk factors or outcomes in men are caused by alcohol exposure rather than by a pleiotropic effect^{8, 9)}.

It remains inconclusive regarding alcohol intake and stroke risk because stroke is a heterogeneous syndrome, and determining risk factors depends on the specific pathogenesis of stroke¹⁰⁾. Intracranial artery stenosis (ICAS) is a large-vessel disease, in which atherosclerotic processes, including the accumulation of lipid-rich plaques, play a major role^{11, 12)}. Lacunar infarcts (LIs), white matter hyperintensities (WMHs), and cerebral microbleeds (CMBs) are small-vessel diseases (SVDs) in which arteriosclerotic processes, including exposure to hypertension and aging, play a major role¹³⁾. The effects of alcohol intake on cardiovascular risk factors are various: for example, higher amount of alcohol intake is associated with higher levels of blood pressure, high-density lipoprotein (HDL) cholesterol, and blood glucose while with lower levels of low-density lipoprotein (LDL) cholesterol^{9, 14-16)}. Therefore, we hypothesize that the effects of alcohol intake differ between pathological types of stroke. In other words, we hypothesize that alcohol intake is positively related to SVD, but negatively related to large-vessel disease.

Aims

In this study, we examined the causal relationships between alcohol consumption and cerebral SVDs (LIs, WMHs, and CMBs) and ICAS as shown by brain magnetic resonance imaging (MRI) among healthy middle-aged to older Japanese men in Mendelian randomization analysis using the ALDH2-rs671 variant. Japanese men have a higher alcohol intake than Western people¹⁷⁾, and approximately 40% to 45% of them have an inactive ALDH2-rs671 A allele^{18, 19)}. Therefore, the Japanese male population is useful for Mendelian randomization analysis using the ALDH2-rs671 variant to investigate the causality between alcohol and the risk of cerebral vessel diseases.

Methods

Study Population

In the present study, we analyzed data from the Shiga Epidemiological Study of Subclinical Atherosclerosis (SESSA), which is a population-based observational study that examined factors affecting subclinical atherosclerosis. The design and enrolment of the SESSA have been previously described²⁰⁾. In brief, 1,094 randomly selected Japanese men based on age strata from Kusatsu City, Shiga, Japan, who were aged 40 to 79 years, participated in baseline examinations (2006-2008). Participants in the baseline survey were then invited for follow-up surveys, including brain MRI scans, in 2012 to 2015, and 740 men agreed to participate in the survey. We excluded 35 men with a history of stroke and 23 whose ALDH2-rs671 genotypes were unavailable. The remaining 682 apparently healthy men (age range, 47-85 years; mean age, 70.0 [standard deviation, 8.8] years) were analyzed in the present study. All participants provided written informed consent. The study was approved by the Institutional Review Board of Shiga University of Medical Science (G2008-061 and G2005-103). The study followed the code of ethics of the World Medical Association (1975 Declaration of Helsinki).

DNA Extraction and Genotyping

Details of the DNA extraction and genotyping procedures have been previously described^{16, 21)}. Genomic DNA was extracted from peripheral blood using the Maxwell Blood DNA purification Kit (Promega Corporation, Madison, WI). The SNP rs671 in ALDH2 was analyzed via the TaqMan probe assay (Applied Biosystems, Waltham, MA). To determine the ALDH2-rs671 genotypes, a commercially available primer and probe were purchased from the Assay-on-Demand system (C_11703892_10). Fluorescence of polymerase chain reaction products was measured using the ABI PRISM 7900HT sequence detector (Applied Biosystems). In all samples, the genotype obtained by sequencing coincided with that analyzed by the TaqMan probe assay.

Alcohol Consumption and Covariate Assessment

We estimated alcohol consumption using a self-administered structured questionnaire²¹⁾ at the follow-up survey (2012-2015). Responses were confirmed by trained nurses. Participants were asked whether they currently drank alcohol, and those who responded “yes” were considered current drinkers. Participants who answered “no” were asked whether they drank regularly in the past. Those who responded “yes” were considered former drinkers, and those who responded “no” were considered never drinkers. Current drinkers, but not former drinkers, were asked to estimate the frequency and amount of alcohol they consumed during a typical week or month. The amount of alcohol was estimated by asking about the size and number of containers or traditional units they typically consumed on one occasion. The unit “go” was used for sake (Japanese traditional rice wine), bottles for beer, glasses for wine, and shots for whisky. One go, which is a traditional Japanese unit of volume, is 180 mL and contains 23 g of ethanol²²⁾, which is similar to two glasses (220 mL) of wine, one medium bottle (500 mL) of beer, or two shots (70 mL) of whisky. Volumes were converted to the estimated amount of ethanol consumed in g/day.

Covariates were assessed at the follow-up survey (2012-2015). Blood samples were obtained early in the clinic visit after a 12-hour fast. Total cholesterol and triglyceride concentrations were measured using enzymatic assays, and HDL cholesterol concentrations were measured using a direct method. The Friedewald formula was used to calculate LDL cholesterol concentrations when triglyceride concentrations were ＜400 mg/dL (i.e., a total of 305 A allele carriers and 361 non-A allele carriers). Plasma glucose concentrations were determined by sodium fluoride-treated plasma using the hexokinase glucose-6 phosphate-dehydrogenase enzymatic assay. Serum gamma-glutamyl transferase (GGT) levels were analyzed with an enzyme kinetic assay. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were measured using the colorimetric assay. These blood measurements were performed at a single laboratory (Shiga Laboratory, MEDIC, Shiga, Japan), which receives annual certification of the standardized lipid measurement in accordance with the protocol of the Centers for Disease Control and Prevention/Cholesterol Reference Method Laboratory Network. Serum high-sensitivity C-reactive protein concentrations were measured by nephelometry on the BN II Analyzer (Siemens Healthineers, Erlangen, Germany). A self-administered questionnaire was also used to obtain information on demographics, smoking habits, exercise, and medication use and history. The number of exercise days each week was calculated on the basis of how many days each week participants regularly engaged in either brisk walking or more active exercise for ≥ 1 hour. The body mass index was calculated as weight (kg) divided by height squared (m²). Using an automated sphygmomanometer (BP-8800; Omron Healthcare Co., Ltd., Kyoto, Japan), blood pressure was measured as the mean of two consecutive measurements on the right arm with participants in a seated position after a 5-minute rest. Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or the use of anti-hypertensive medication²³⁾. Diabetes mellitus was defined as fasting blood glucose concentrations ≥ 126 mg/dL or the use of anti-diabetic medication²⁴⁾.

MRI Protocol and Image Analysis

Details for the assessment of cerebral vessel diseases have been previously described^{25, 26)}. MRI was performed using a 1.5-Tesla magnetic resonance scanner (Signa HDxt 1.5T ver. 16; GE Healthcare, Milwaukee, WI) at the follow-up survey (2012-2015). Two neurosurgeons (K.N., A.S.), certified by the Japan Neurosurgery Society, independently assessed all MRI images in duplicate. Disagreements in assessments were resolved with adjudication by the neurosurgeons. LIs were defined as low signal intensity areas on T1-weighted images, with a size of 3 to 15 mm, and visible as hyperintense lesions on T2-weighted images. The irregular shapes of the lacunars in high-resolution three-dimensional T1-weighted spoiled gradient recalled and their surrounding gliosis in fluid-attenuated inversion-recovery sequence (FLAIR) images were considered when differentiating these lesions from enlarged perivascular spaces. LIs of each anatomical segment (basal ganglia, brainstem, thalamus, white matter, and other areas) were counted and graded as 0, 1 to 2, or ≥ 3. WMHs were defined as hyperintense regions on FLAIR images and sub-grouped into either deep and subcortical white matter hyperintensities (DSWMHs) or periventricular hyperintensities (PVHs). WMHs were then graded in accordance with the classification proposed by Shinohara et al ²⁷⁾, which was adopted by the Japanese Brain Dock Guidelines in 2014 ²⁸⁾, and is similar to that proposed by Fazekas et al ²⁹⁾. CMBs were defined as hypointense (or signal void) lesions on T2*-weighted images. We counted the number of CMBs for each of the following anatomical segments: white matter, basal ganglia, cerebral cortex, cerebellum, brainstem, and thalamus. For the assessment of ICAS, 11 intracranial arteries (basilar artery plus the following 5 vessels bilaterally: intracranial segments of the internal carotid artery, middle cerebral artery, anterior cerebral artery, intracranial segments of the vertebral artery, and posterior cerebral artery) were evaluated. In each artery, the ordinal degree of narrowing was graded as no detectable stenosis, 1% to 49% stenosis, and 50% to 100% stenosis using the criteria established in the Warfarin–Aspirin Symptomatic Intracranial Disease trial³⁰⁾.

Statistical Analysis

The rationale behind Mendelian randomization analysis is that genetic variation associated with a risk factor may serve as a proxy for exposure to varying doses of that metabolic trait⁷⁾. Therefore, an association between a genetic variant and both the risk factor and disease outcome implies a causal association between the risk factor and disease outcome. We used the ALDH2-rs671 variant as a robust genetic instrument of alcohol consumption in our Mendelian randomization analysis. In general, Mendelian randomization studies are less vulnerable to bias from confounding, reverse causation, and measurement error compared with conventional observational studies⁷⁾.

In all analyses, we used a dominant model because of the low prevalence of ALDH2-rs671 A allele homozygotes (n=58 [8.5%]). Data from carriers of either one or two A alleles were pooled and compared with individuals who were homozygous for the G allele (i.e., inactive A allele carriers [GA and AA] vs. non-A allele carriers [GG]). The differences in characteristics between the ALDH2-rs671 genotypes were compared using the unpaired Student’s t-test, Mann–Whitney U test, or χ² test. We used ordinal logistic regression to estimate the odds ratios and 95% confidence intervals between A allele carriers (as a reference) and non-A allele carriers for the graded distributions of the following cerebral vessel diseases: total SVDs (number of SVDs, 0; 1; 2; and 3), LIs (number of lesions, 0; 1 or 2; and ≥ 3)³¹⁾; WMHs (grade of PVHs or DSWMHs, 0 or 1; 2; and ≥ 3)^{32, 33)}; CMBs (number of lesions, 0; 1; and ≥ 2); and ICAS (grade of stenosis, 0; 1%-49%; and 50%-100%)^{26, 34)}, defined according to their clinical significance and consistency with previous studies. In Model 1, we adjusted for age. In Model 2, we subsequently adjusted for age, smoking (former, current), body mass index, hypertension, LDL cholesterol, HDL cholesterol, statins, diabetes mellitus, and C-reactive protein. We recognized a priori that Model 2 may introduce overcorrection/overmodelling because some covariates (e.g., hypertension and LDL cholesterol) could be intermediaries in the causal pathway between alcohol consumption and cerebral vessel diseases. In Model 3, we further adjusted for the amount of alcohol intake to determine whether the amount of drinking can explain the genetic association with cerebral SVD and large-vessel disease. We adjusted each factor (body mass index, smoking status, hypertension, LDL cholesterol, HDL cholesterol, statins use, diabetes mellitus, and C-reactive protein) one by one in addition to age in the model to examine how much each factor accounted for the association of ALHD2-rs671 genotype with cerebral vessel diseases. We divided non-A allele carriers into the two groups of light (＜20g alcohol intake / day) and heavy (≥ 20g alcohol intake / day) drinkers, and subsequently, we compared the association with cerebral SVDs and large-vessel disease between A-allele carriers, and light- and heavy-drinking non-A allele carriers to determine dose-dependent relationships between alcohol consumption and cerebral SVDs and large-vessel disease. Using a sensitivity analysis, we also examined the presence of total SVDs, LIs, WMHs, CMBs, and ICAS as dependent variables in Poisson regression with robust error variance³⁵⁾. Because the prevalence of cerebral SVDs and ICAS as defined above was ＞10% in our cohort, odds ratios could not be interpreted as relative risks. Therefore, we used a Poisson regression with robust error variance to estimate the relative risks for prevalent cerebral SVDs and ICAS. The analyses were performed using a statistical program (STATA, version 16.0; StataCorp LP, College Station, TX). Two-tailed P values of ＜0.05 were considered statistically significant.

Results

Among the study participants, there were 313 (45.9%) ALDH2-rs671 inactive A allele carriers and 369 (54.1%) non-A allele carriers. The characteristics of the participants according to the ALDH2-rs671 genotype are shown in Table 1. The median (25%tile, 75%tile) amount of alcohol consumption by A allele and non-A allele carriers was 3.5 (0.0, 16.0) g/day and 32.0 (12.9, 50.0) g/day, respectively. Almost all (95.4%) non-A allele carriers were also current drinkers. Non-A allele carriers had higher systolic and diastolic blood pressure, higher fasting blood glucose concentrations, higher GGT, AST, and ALT levels, a higher prevalence of anti-hypertensive medication use and hypertension, and lower LDL cholesterol concentrations than A allele carriers.

Table 1.Characteristics of 682 male participants aged 47 to 85 years according to the ALDH2-rs671 genotype (SESSA, Shiga, Japan, 2012–2015)

	ALDH2-rs671		P
	A allele carriers n = 313	Non-A allele carriers n = 369
Age, years	70.0 (8.7)	69.5 (9.0)	0.451
Body mass index, kg/m2	23.2 (2.7)	23.4 (3.0)	0.507
Smoking status, %			0.117
Former	59.4	59.0
Current	17.3	22.6
Exercise, %＊	56.6	56.6	0.981
Blood pressure, mmHg
Systolic	130.6 (16.6)	133.2 (17.1)	0.041
Diastolic	76.2 (10.3)	78.1 (10.6)	0.017
Antihypertensive medication, %	33.6	41.1	0.042
Hypertension, %†	50.8	59.9	0.017
Total cholesterol, mg/dL	204.9 (33.5)	200.3 (34.9)	0.087
Triglycerides, mg/dL	99 (73, 136)	104 (72, 145)	0.419
HDL cholesterol, mg/dL	58.4 (16.0)	60.4 (16.9)	0.109
LDL cholesterol, mg/dL‡	123.0 (30.0)	114.7 (33.4)	＜0.001
Statin, %	18.2	15.2	0.288
Glucose, mg/dL	100.4 (19.1)	103.8 (24.0)	0.044
Antidiabetic medication, %	14.4	15.5	0.696
Diabetes mellitus, %§	17.6	20.1	0.409
C-reactive protein, mg/dL	0.45 (0.24, 0.93)	0.46 (0.25, 1.01)	0.456
GGT, U/L	27 (20, 42)	38 (26, 62)	＜0.001
AST, U/L	23 (20, 28)	25 (21, 31)	＜0.001
ALT, U/L	19 (15, 25)	21 (16, 29)	＜0.001
Alcohol intake, g/day	3.5 (0.0, 16.0)	32.0 (12.9, 50.0)	＜0.001
Drinking status, %			＜0.001
Never	29.2	1.4
Former	5.1	3.2
Current	65.7	95.4

Data are presented as mean (standard deviation) or median (25%tile, 75%tile) unless otherwise specified.

^＊Participants who exercised were defined as those who regularly engaged in either brisk walking or more active exercise for ≥ 1 hour/ week. ^†Hypertension was defined as systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or the use of anti- hypertensive medication. ^‡LDL cholesterol was estimated using the Friedewald formula in 305 and 361 participants who were A allele and non-A allele carriers, respectively, who had triglyceride concentrations ＜400 mg/dL. ^§Diabetes mellitus was defined as fasting blood glucose concentrations ≥ 126 mg/dL or the use of anti-diabetic medication.

ALDH2, Aldehyde dehydrogenase 2; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, gamma-glutamyl transferase; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SESSA, Shiga Epidemiological Study of Subclinical Atherosclerosis.

The association of graded distributions of cerebral vessel diseases as observed by brain MRI with the ALDH2-rs671 genotype is shown in Table 2. In ordinal logistic regression adjusted for age (Model 1), the odds ratios (95% confidence intervals) for total SVDs, LIs, WMHs, CMBs, and ICAS in non-A allele carriers were 1.46 (1.09-1.94), 1.41 (0.95-2.08), 1.39 (1.05-1.85), 1.69 (1.06-2.69), and 0.70 (0.50-0.98), respectively, compared with ALDH2-rs671 A allele carriers. These associations were attenuated to marginal significance after multivariable adjustment (Model 2) and became completely non-significant after further considering the amount of alcohol intake (Model 3). When each factor was adjusted one by one in addition to age in the model, for SVDs including LIs, WMHs, and CMBs, the association of the ALDH2-rs671 genotype in age-adjusted model was most attenuated by further adjustment for hypertension, while for ICAS, its association was most attenuated by further adjustment for LDL cholesterol (Supplementary Table 1). We found dose-dependent relationships of A-allele carriers, and light- and heavy-drinking non-A allele carriers to cerebral SVDs and large-vessel disease in age-adjusted model (all P values for trend ＜0.05 in Model 1) (Supplementary Table 2). Heavy-drinking non-A allele carriers had significantly higher odds for cerebral SVDs including LIs, WMHs, CMBs and lower odds for ICAS than A allele carriers. These associations were also attenuated after taking into account covariates and the actual amount of alcohol intake.

Table 2.Association of graded distributions of cerebral vessel diseases as shown by brain MRI with the ALDH2-rs671 genotype

		ALDH2-rs671		P
		A allele carriers n = 313	Non-A allele carriers n = 369
Total SVDs	Number of SVDs, no. (%)
	1	151 (48.2)	182 (49.3)
	2	51 (16.3)	68 (18.4)
	3	10 (3.2)	24 (6.5)
	Crude model, odds ratio (95% CI)	1 (ref )	1.39 (1.05-1.85)	0.022
	Model 1, odds ratio (95% CI)	1 (ref )	1.46 (1.09-1.94)	0.010
	Model 2, odds ratio (95% CI)	1 (ref )	1.33 (0.99-1.79)	0.057
	Model 3, odds ratio (95% CI)	1 (ref )	1.29 (0.93-1.79)	0.121
LIs	Number of lesions, no. (%)
	1 or 2	48 (15.3)	63 (17.1)
	3 or more	8 (2.6)	18 (4.9)
	Crude model, odds ratio (95% CI)	1 (ref )	1.31 (0.90-1.92)	0.158
	Model 1, odds ratio (95% CI)	1 (ref )	1.41 (0.95-2.08)	0.089
	Model 2, odds ratio (95% CI)	1 (ref )	1.20 (0.80-1.82)	0.375
	Model 3, odds ratio (95% CI)	1 (ref )	1.18 (0.75-1.86)	0.468
WMHs	Grade, no. (%)
	2	114 (36.4)	131 (35.5)
	3 or 4	81 (25.9)	121 (32.8)
	Crude model, odds ratio (95% CI)	1 (ref )	1.35 (1.02-1.78)	0.036
	Model 1, odds ratio (95% CI)	1 (ref )	1.39 (1.05-1.85)	0.021
	Model 2, odds ratio (95% CI)	1 (ref )	1.32 (0.99-1.76)	0.058
	Model 3, odds ratio (95% CI)	1 (ref )	1.30 (0.95-1.78)	0.107
CMBs	Number of lesions, no. (%)
	1	24 (7.7)	37 (10.0)
	2 or more	8 (2.6)	20 (5.4)
	Crude model, odds ratio (95% CI)	1 (ref )	1.62 (1.02-2.58)	0.039
	Model 1, odds ratio (95% CI)	1 (ref )	1.69 (1.06-2.69)	0.028
	Model 2, odds ratio (95% CI)	1 (ref )	1.60 (0.99-2.58)	0.056
	Model 3, odds ratio (95% CI)	1 (ref )	1.52 (0.90-2.56)	0.116
ICAS	Grade of stenosis, no. (%)
	1% to 49%	78 (24.9)	75 (20.3)
	50 to 100%	22 (7.0)	18 (4.9)
	Crude model, odds ratio (95% CI)	1 (ref )	0.69 (0.49-0.96)	0.029
	Model 1, odds ratio (95% CI)	1 (ref )	0.70 (0.50-0.98)	0.039
	Model 2, odds ratio (95% CI)	1 (ref )	0.70 (0.49-1.00)	0.052
	Model 3, odds ratio (95% CI)	1 (ref )	0.76 (0.51-1.13)	0.179

This analysis was based on ordinal logistic regression with odds ratios and 95% confidence intervals (CIs) in non-A allele carriers vs. inactive A allele carriers of the aldehyde dehydrogenase 2 (ALDH2)-rs671 genotype.

In all participants (n = 682), Model 1 was adjusted for age; in participants with triglyceride concentrations ＜400 mg/dL (n = 666), Model 2 was adjusted for age, smoking, body mass index, hypertension, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, statins, diabetes mellitus, and C-reactive protein; and Model 3 was further adjusted for the amount of alcohol intake in addition to Model 2.

CMB, cerebral microbleed; ICAS, intracranial artery stenosis; LI, lacunar infarct; MRI, magnetic resonance imaging; SVD, small-vessel disease; WMH, white matter hyperintensity.

Supplementary Table 1.Odds ratios with 95% CI for graded distributions of cerebral vessel diseases by the ALDH2-rs671 genotype, adjusted for each factor one by one in addition to age

		ALDH2-rs671		P
		A allele carriers	Non-A allele carriers
Total SVDs	Age-adjusted	1 (ref )	1.46 (1.09-1.94)	0.010
	+ body mass index	1 (ref )	1.45 (1.09-1.93)	0.012
	+ smoking status	1 (ref )	1.43 (1.07-1.90)	0.016
	+ hypertension	1 (ref )	1.40 (1.05-1.87)	0.022
	+ LDL cholesterol	1 (ref )	1.44 (1.08-1.92)	0.014
	+ HDL cholesterol	1 (ref )	1.46 (1.09-1.95)	0.011
	+ statin use	1 (ref )	1.46 (1.09-1.95)	0.010
	+ diabetes mellitus	1 (ref )	1.45 (1.09-1.94)	0.011
	+ C-reactive protein	1 (ref )	1.45 (1.09-1.94)	0.011
LIs	Age-adjusted	1 (ref )	1.41 (0.95-2.08)	0.089
	+ body mass index	1 (ref )	1.40 (0.95-2.08)	0.089
	+ smoking status	1 (ref )	1.39 (0.94-2.06)	0.100
	+ hypertension	1 (ref )	1.29 (0.87-1.92)	0.211
	+ LDL cholesterol	1 (ref )	1.31 (0.88-1.95)	0.182
	+ HDL cholesterol	1 (ref )	1.42 (0.96-2.10)	0.082
	+ statin use	1 (ref )	1.43 (0.97-2.12)	0.073
	+ diabetes mellitus	1 (ref )	1.40 (0.95-2.08)	0.093
	+ C-reactive protein	1 (ref )	1.41 (0.95-2.08)	0.088
WMHs	Age-adjusted	1 (ref )	1.39 (1.05-1.85)	0.021
	+ body mass index	1 (ref )	1.39 (1.05-1.84)	0.022
	+ smoking status	1 (ref )	1.38 (1.04-1.83)	0.025
	+ hypertension	1 (ref )	1.36 (1.02-1.80)	0.035
	+ LDL cholesterol	1 (ref )	1.42 (1.07-1.89)	0.016
	+ HDL cholesterol	1 (ref )	1.39 (1.05-1.84)	0.023
	+ statin use	1 (ref )	1.38 (1.04-1.83)	0.024
	+ diabetes mellitus	1 (ref )	1.39 (1.05-1.85)	0.021
	+ C-reactive protein	1 (ref )	1.40 (1.06-1.86)	0.019
CMBs	Age-adjusted	1 (ref )	1.69 (1.06-2.69)	0.028
	+ body mass index	1 (ref )	1.68 (1.06-2.68)	0.029
	+ smoking status	1 (ref )	1.71 (1.07-2.72)	0.025
	+ hypertension	1 (ref )	1.62 (1.01-2.60)	0.040
	+ LDL cholesterol	1 (ref )	1.62 (1.01-2.60)	0.040
	+ HDL cholesterol	1 (ref )	1.67 (1.04-2.66)	0.033
	+ statin use	1 (ref )	1.7 (1.07-2.71)	0.026
	+ diabetes mellitus	1 (ref )	1.69 (1.06-2.69)	0.028
	+ C-reactive protein	1 (ref )	1.65 (1.04-2.64)	0.035
ICAS	Age-adjusted	1 (ref )	0.70 (0.50-0.98)	0.039
	+ body mass index	1 (ref )	0.70 (0.50-0.98)	0.037
	+ smoking status	1 (ref )	0.70 (0.50-0.98)	0.037
	+ hypertension	1 (ref )	0.63 (0.45-0.89)	0.009
	+ LDL cholesterol	1 (ref )	0.73 (0.52-1.03)	0.070
	+ HDL cholesterol	1 (ref )	0.72 (0.51-1.02)	0.064
	+ statin use	1 (ref )	0.71 (0.51-1.00)	0.051
	+ diabetes mellitus	1 (ref )	0.69 (0.49-0.96)	0.030
	+ C-reactive protein	1 (ref )	0.69 (0.49-0.97)	0.030

This analysis was based on ordinal logistic regression with odds ratios and 95% confidence intervals (CIs) in non-A allele carriers vs. inactive A allele carriers of the aldehyde dehydrogenase 2 (ALDH2)-rs671 genotype.

CMB, cerebral microbleed; HDL, high-density lipoprotein; ICAS, intracranial artery stenosis; LI, lacunar infarct; LDL, low-density lipoprotein; SVD, small-vessel disease; WMH, white matter hyperintensity.

Supplementary Table 2.Association of cerebral SVDs and large-vessel disease as shown by brain MRI between A-allele carriers, and light- and heavy-drinking non-A allele carriers

		ALDH2-rs671			P for trend
		A allele carriers n = 313	Non-A allele carriers
			Light drinking ＜20g / day n = 127	Heavy drinking ≥ 20g / day n = 242
Total SVDs	Number of SVDs, no. (%)
	1	151 (48.2)	59 (46.5)	123 (50.8)
	2	51 (16.3)	21 (16.5)	47 (19.4)
	3	10 (3.2)	6 (4.7)	18 (7.4)
	Crude model, odds ratio (95% CI)	1 (ref )	1.05 (0.71-1.55)	1.61 (1.18-2.21)†	0.004
	Model 1, odds ratio (95% CI)	1 (ref )	1.12 (0.75-1.66)	1.67 (1.21-2.30)†	0.002
	Model 2, odds ratio (95% CI)	1 (ref )	1.10 (0.74-1.64)	1.49 (1.07-2.09)＊	0.021
	Model 3, odds ratio (95% CI)	1 (ref )	1.09 (0.73-1.63)	1.60 (1.03-2.47)＊	0.048
LIs	Number of lesions, no. (%)
	1 or 2	48 (15.3)	21 (16.5)	42 (17.4)
	3 or more	8 (2.6)	4 (3.2)	14 (5.8)
	Crude model, odds ratio (95% CI)	1 (ref )	1.13 (0.67-1.90)	1.42 (0.94-2.14)	0.100
	Model 1, odds ratio (95% CI)	1 (ref )	1.11 (0.64-1.91)	1.59 (1.03-2.44)＊	0.037
	Model 2, odds ratio (95% CI)	1 (ref )	1.08 (0.62-1.87)	1.29 (0.81-2.05)	0.292
	Model 3, odds ratio (95% CI)	1 (ref )	1.07 (0.62-1.87)	1.34 (0.73-2.48)	0.366
WMHs	Grade, no. (%)
	2	114 (36.4)	39 (30.7)	92 (38.0)
	3 or 4	81 (25.9)	37 (29.1)	84 (34.7)
	Crude model, odds ratio (95% CI)	1 (ref )	1.01 (0.69-1.48)	1.56 (1.14-2.12)†	0.006
	Model 1, odds ratio (95% CI)	1 (ref )	1.06 (0.72-1.57)	1.60 (1.17-2.18)†	0.004
	Model 2, odds ratio (95% CI)	1 (ref )	1.07 (0.72-1.59)	1.49 (1.07-2.06)＊	0.020
	Model 3, odds ratio (95% CI)	1 (ref )	1.06 (0.72-1.58)	1.65 (1.08-2.53)＊	0.033
CMBs	Number of lesions, no. (%)
	1	24 (7.7)	12 (9.5)	25 (10.3)
	2 or more	8 (2.6)	6 (4.7)	14 (5.8)
	Crude model, odds ratio (95% CI)	1 (ref )	1.46 (0.79-2.71)	1.71 (1.04-2.82)＊	0.035
	Model 1, odds ratio (95% CI)	1 (ref )	1.50 (0.80-2.80)	1.79 (1.08-2.96)＊	0.024
	Model 2, odds ratio (95% CI)	1 (ref )	1.34 (0.71-2.54)	1.77 (1.04-3.02)＊	0.035
	Model 3, odds ratio (95% CI)	1 (ref )	1.34 (0.71-2.54)	1.78 (0.89-3.56)	0.089
ICAS	Grade of stenosis, no. (%)
	1% to 49%	78 (24.9)	28 (22.1)	47 (19.4)
	50 to 100%	22 (7.0)	7 (5.5)	11 (4.6)
	Crude model, odds ratio (95% CI)	1 (ref )	0.76 (0.48-1.21)	0.65 (0.45-0.95)＊	0.026
	Model 1, odds ratio (95% CI)	1 (ref )	0.76 (0.48-1.22)	0.67 (0.46-0.98)＊	0.036
	Model 2, odds ratio (95% CI)	1 (ref )	0.69 (0.42-1.13)	0.71 (0.47-1.07)	0.079
	Model 3, odds ratio (95% CI)	1 (ref )	0.68 (0.41-1.11)	0.89 (0.51-1.56)	0.352

This analysis was based on ordinal logistic regression with odds ratios and 95% confidence intervals (CIs) in light- and heavy-drinking non-A allele carriers vs. inactive A allele carriers of the aldehyde dehydrogenase 2 (ALDH2)-rs671 genotype. In all participants (n = 682), Model 1 was adjusted for age; in participants with triglyceride concentrations ＜400 mg/dL (n = 666), Model 2 was adjusted for age, smoking, body mass index, hypertension, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, statins, diabetes mellitus, and C-reactive protein; and Model 3 was further adjusted for the amount of alcohol intake in addition to Model 2.

P values: ^＊＜0.05; ^†＜0.01. CMB, cerebral microbleed; ICAS, intracranial artery stenosis; LI, lacunar infarct; MRI, magnetic resonance imaging; SVD, small-vessel disease; WMH, white matter hyperintensity.

The association of the presence of cerebral vessel diseases as observed by brain MRI with the ALDH2-rs671 genotype is shown in Table 3. In Poisson regression with robust error variance adjusted for age (Model 1), non-A allele carriers had relative risks (95% confidence intervals) of 1.11 (1.01-1.22) for total SVDs, 1.26 (0.93-1.69) for LIs, 1.11 (0.99-1.23) for WMHs, 1.54 (1.03-2.30) for CMBs, and 0.78 (0.62-0.99) for ICAS compared with ALDH2-rs671 A allele carriers. These associations were attenuated and became statistically non-significant after multivariable adjustment or further considering the amount of alcohol intake (Models 2 and 3).

Table 3.Association of the presence of cerebral vessel diseases as shown by brain MRI with the ALDH2-rs671 genotype

	ALDH2-rs671		P
	A allele carriers n = 313	Non-A allele carriers n = 369
Total SVDs, no. (%)	212 (67.7)	274 (74.3)
Crude model, relative risk (95% CI)	1 (ref )	1.10 (0.99-1.21)	0.064
Model 1, relative risk (95% CI)	1 (ref )	1.11 (1.01-1.22)	0.037
Model 2, relative risk (95% CI)	1 (ref )	1.08 (0.98-1.18)	0.131
Model 3, relative risk (95% CI)	1 (ref )	1.06 (0.95-1.18)	0.297
LIs, no. (%)	56 (17.9)	81 (22.0)
Crude model, relative risk (95% CI)	1 (ref )	1.23 (0.90-1.67)	0.190
Model 1, relative risk (95% CI)	1 (ref )	1.26 (0.93-1.69)	0.130
Model 2, relative risk (95% CI)	1 (ref )	1.11 (0.82-1.50)	0.513
Model 3, relative risk (95% CI)	1 (ref )	1.10 (0.79-1.53)	0.573
WMHs, no. (%)	195 (62.3)	252 (68.3)
Crude model, relative risk (95% CI)	1 (ref )	1.10 (0.98-1.22)	0.104
Model 1, relative risk (95% CI)	1 (ref )	1.11 (0.99-1.23)	0.072
Model 2, relative risk (95% CI)	1 (ref )	1.08 (0.97-1.20)	0.184
Model 3, relative risk (95% CI)	1 (ref )	1.05 (0.93-1.19)	0.395
CMBs, no. (%)	32 (10.2)	57 (15.5)
Crude model, relative risk (95% CI)	1 (ref )	1.51 (1.01-2.27)	0.046
Model 1, relative risk (95% CI)	1 (ref )	1.54 (1.03-2.30)	0.036
Model 2, relative risk (95% CI)	1 (ref )	1.46 (0.96-2.22)	0.074
Model 3, relative risk (95% CI)	1 (ref )	1.40 (0.89-2.18)	0.144
ICAS, no. (%)	100 (32.0)	93 (25.2)
Crude model, relative risk (95% CI)	1 (ref )	0.77 (0.60-0.98)	0.033
Model 1, relative risk (95% CI)	1 (ref )	0.78 (0.62-0.99)	0.043
Model 2, relative risk (95% CI)	1 (ref )	0.79 (0.63-1.00)	0.050
Model 3, relative risk (95% CI)	1 (ref )	0.84 (0.65-1.07)	0.161

This analysis was based on Poisson regression with robust error variance with relative risks and 95% confidence intervals (CIs) in non-A allele carriers vs. inactive A allele carriers of the aldehyde dehydrogenase 2 (ALDH2)-rs671 genotype.

In all participants (n = 682), Model 1 was adjusted for age; in participants with triglyceride concentrations ＜400 mg/dL (n = 666), Model 2 was adjusted for age, smoking, body mass index, hypertension, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, statins, diabetes mellitus, and C-reactive protein; and Model 3 was further adjusted for the amount of alcohol intake in addition to Model 2.

CMB, cerebral microbleed; ICAS, intracranial artery stenosis; LI, lacunar infarct; MRI, magnetic resonance imaging; SVD, small-vessel disease; WMH, white matter hyperintensity.

Discussion

In our study, the ALDH2-rs671 variant, which greatly alters alcohol metabolism, was common in Japanese men. Additionally, inactive A allele carriers showed markedly reduced alcohol consumption (nearly to zero), whereas non-A allele carriers showed high alcohol consumption. Therefore, the ALDH2-rs671 variant can be used as a robust genetic instrument of alcohol consumption in Mendelian randomization analysis. This variant allows for a reliable examination of the causal association between alcohol consumption and the risk of cerebral vessel diseases.

The main finding in our study is that ALDH2-rs671 non-A allele carriers had a higher burden of cerebral SVDs (LIs, WMHs, and CMBs) and a lower burden of large-vessel disease (ICAS) than did A allele carriers. These associations were attenuated to statistical non-significance after taking into account covariates and the actual amount of alcohol intake. We also found dose-dependent relationships between alcohol consumption and cerebral SVDs and large-vessel disease. Therefore, our findings suggest an association of high alcohol consumption with an increased risk of SVDs and an inverse association of alcohol consumption with a risk of ICAS. These associations could occur through intermediaries in the causal pathway between alcohol intake and cerebral vessel diseases. In particular, hypertension and LDL cholesterol would be ones of the major intermediaries in the causal pathway from alcohol consumption to cerebral SVDs and large-vessel disease, respectively.

The differential association between cerebral SVD and large-vessel disease could be explained by the discrepancies in the pathogenesis of cerebral SVD and large-vessel disease. Large-vessel disease, such as ICAS, is a manifestation in which atherosclerotic processes, including the accumulation of lipid-rich plaques, play a major role^{11, 12)}. However, SVD, such as LIs, WMHs, and CMBs, is a condition in which arteriosclerosis processes, including exposure to hypertension, play a major role¹³⁾. Alcohol intake may increase the risk of SVD and decrease the risk of ICAS because of the heterogeneous associations of alcohol intake across risk factors (i.e., increasing BP levels while decreasing LDL cholesterol concentrations)^{9, 14-16)}. Interestingly, consistent with prior findings based on a meta-analysis of interventional studies or Mendelian randomization studies^{9, 14-16)}, our results indicate associations of higher alcohol consumption with higher BP levels and lower LDL cholesterol concentrations.

Randomized, controlled trials to confirm or refute the effect of alcohol on the risk of cardiovascular disease have not been performed. These trials have not been performed because of unethical aspects related to the enrolment of participants being randomly assigned to certain alcohol exposures. However, a series of Mendelian randomization studies have been performing using the ALDH2-rs671 variant. A 10-year prospective study of almost 500,000 Chinese people based on Mendelian randomization analysis showed a positive association of alcohol consumption with the risk of ischemic, hemorrhagic, or total stroke⁹⁾. Notably, East Asian populations have a high prevalence of ischemic or hemorrhagic stroke due to SVDs, but a low prevalence of ischemic stroke due to large-vessel disease³⁶⁾. Therefore, the findings from Mendelian randomization analysis, including our study, indicate a causal role of alcohol consumption with a higher risk of stroke through a higher burden of SVDs.

The SNP rs1229984 in the alcohol dehydrogenase 1B gene (ADH1B), which encodes the ADH1B enzyme, provides another primary pathway of alcohol metabolism. However, it is less important than ALDH2-rs671⁹⁾. Indeed, a Mendelian randomization meta-analysis using ADH1B-rs1229984 could not directly compared the effect of negligible versus moderate/high alcohol intake levels for cardiovascular disease risk³⁷⁾.

Several limitations of the present study warrant consideration. First, we only studied middle-aged to older men, and the sample was obtained from a single area in Japan, both of which may limit the generalizability of the present results. Second, we did not have a replication cohort to verify our findings. However, our results are consistent and support the results from the previous Mendelian randomization study using ALDH2-rs671 on alcohol consumption and the risk of stroke⁹⁾. Third, visual ratings of LIs, WMHs, CMBs, and ICAS may have introduced some potential errors (e.g., misclassification), which cannot be ignored. Finally, the relatively small sample size may have contributed to the lack of power in some analyses (e.g., difference in HDL cholesterol levels between the groups or odds ratio/relative risk for LIs). Collaborations of randomized, controlled trials on quitting alcohol at different levels or those of Mendelian randomization studies that use the ALDH2-rs671 variant as a genetic instrument are ethical, informative, and warranted.

Conclusions

In conclusion, our findings indicate an association of high alcohol consumption with an increased risk of cerebral SVDs and an inverse association of alcohol consumption with the risk of large-vessel disease. These associations could occur through intermediaries, such as hypertension and LDL cholesterol. Our Mendelian randomization analysis provides insight into potential causal mechanisms linking alcohol consumption with the risk of cerebral vessel diseases. Additionally, our findings emphasize the importance of reducing alcohol consumption for the prevention of high blood pressure and stroke through a higher burden of SVDs.

Acknowledgements

We thank the SESSA investigators, staff, and study participants for their commitments and outstanding dedication. A full list of the SESSA investigators can be found at https://hs-web.shiga-med.ac.jp/sessa/research/. We thank Ellen Knapp, PhD, from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.

Sources of Funding

This work was supported by Grants-in-aid for Scientific Research (grant numbers A13307016, A17209023, A21249043, A23249036, A25253046, A15H02528, 17K15827, 18H04074, and 22H00493) from the Ministry of Education, Culture, Sports, Science and Technology Japan, and by the National Institutes of Health, USA (grant number R01HL068200). The funding sources listed above have no role in the study design, collection, analyses, and interpretation of the results.

Conflict of Interest

None.

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