Abstract
Background
Gout stems from both modifiable and genetic sources. We evaluated the risk of gout among Taiwanese adults with aldehyde dehydrogenase-2 (ALDH2) rs671 single nucleotide polymorphism (SNP) according to body mass index (BMI) and alcohol drinking.
Methods
We obtained information of 9253 individuals having no personal history of cancer from the Taiwan Biobank (2008–2016) and estimated the association between gout and independent variables (e.g., rs671, BMI, and alcohol drinking) using multiple logistic regression.
Results
Alcohol drinking and abnormal BMI were associated with a higher risk of gout whereas the rs671 GA+AA genotype was associated with a lower risk. The odds ratios (ORs) and 95% confidence intervals (CIs) were 1.297 and 1.098–1.532 for alcohol drinking, 1.550 and 1.368–1.755 for abnormal BMI, and 0.887 and 0.800–0.984 for GA+AA. The interaction between BMI and alcohol on gout was significant for GG (p-value = 0.0102) and GA+AA (p-value = 0.0175). When we stratified genotypes by BMI, alcohol drinking was significantly associated with gout only among individuals with a normal BMI (OR; 95% CI = 1.533; 1.036–2.269 for GG and 2.109; 1.202–3.699 for GA+AA). Concerning the combination of BMI and alcohol drinking among participants stratified by genotypes (reference, GG genotype, normal BMI, and no alcohol drinking), the risk of gout was significantly higher in the following categories: GG, normal BMI, and alcohol drinking (OR, 95% CI = 1.929, 1.385–2.688); GG, abnormal BMI, and no alcohol drinking (OR, 95% CI, = 1.721, 1.442–2.052); GG, abnormal BMI, and alcohol drinking (OR, 95% CI = 1.941, 1.501–2.511); GA+AA, normal BMI, and alcohol drinking (OR, 95% CI = 1.971, 1.167–3.327); GA+AA, abnormal BMI, and no alcohol drinking (OR, 95% CI = 1.498, 1.256–1.586); and GA+AA, abnormal BMI, and alcohol drinking (OR, 95% CI = 1.545, 1.088–2.194).
Conclusions
Alcohol and abnormal BMI were associated with a higher risk of gout, whereas the rs671 GA+AA genotype was associated with a lower risk. Noteworthy, BMI and alcohol had a significant interaction on gout risk. Stratified analyses revealed that alcohol drinking especially among normal-weight individuals might elevate the risk of gout irrespective of the genotype.
Keywords: Alcohol drinking; BMI, ALDH2; rs671; Gout; Taiwan biobank
Background
Gout is a metabolic disease that results from monosodium urate crystal deposits that are generally associated with high levels of urate serum [1, 2]. It is common worldwide and its incidence and prevalence are purportedly increasing [3]. Taiwan is among the top-tiered countries with a high prevalence of gout in the world [3, 4]. Data from Nutrition and Health Survey in Taiwan (NAHSIT) from 1993–1996 to 2005–2008 showed an increase in the prevalence of gout from 4.74 to 8.21% in men and 2.19 to 2.33% in women [5]. Moreover, a nationwide study revealed a prevalence of 6.24% and an incidence of 2.74 per 1000 person-years in 2010 [4].
Previous epidemiological studies identified numerous gout-related modifiable and non-modifiable factors, including but not limited to alcohol intake, BMI, cigarette smoking, sex, age, uric acid, and single nucleotide polymorphism [1, 2, 6–9]. BMI, a modifiable risk factor for gout [2, 3, 7, 8, 10, 11], is also related to well-established major risk factors for gout like hyperuricemia and alcohol consumption [3, 9, 12–15]. Alcohol is a proven key modifiable factor that has been specifically linked to higher incidence and prevalence of gout [2, 7, 8, 10, 11, 13, 16]. It is also a driving factor for hyperuricemia [17], a well-known precursor for gout [1, 2]. Alcohol could influence the risk of gout through its effect on uric acid [18–20]. ALDH2 rs671 attained genome-wide significance as a genetic locus for alcohol drinking [21].
ALDH2 is a vital enzyme in the metabolism of alcohol [22, 23]. The ALDH2 variant, rs671 is a missense SNP that impedes the enzymatic activity of the ALDH2, probably impacting metabolism that results in uric acid synthesis [24]. ALDH2 polymorphisms contribute not only to the metabolism of ethanol and acetaldehyde [25] but also impact predisposition to alcohol-related morbid conditions like hyperuricemia and gout among Asians [18, 19, 26–28]. The link between ALDH2 polymorphisms and serum urate was found to be mediated by alcohol intake among Han Chinese men [19]. ALDH2 rs671 is proven gout-related SNP [22, 29, 30].
Insights into interconnections between modifiable and genetic factors could aid in both the prevention and management of diseases. So far, a meta-analysis revealed that alcohol intake could modulate the link between BMI and ALDH2 rs671 among Koreans and Chinese [31]. Moreover, findings from GWAS suggest that BMI-associated alleles of rs671 are also linked to alcohol drinking behavior [25] and alcohol clearance [23]. The role of both BMI and alcohol drinking in the risk of gout according to ALDH2 rs671 genotypes has not been sufficiently investigated. As such, it is currently inconclusive whether the risk of gout varies based on the combination of these variables. In this study, we evaluated ALDH-2 rs671 polymorphism and the risk of gout according to two modifiable factors (BMI and alcohol intake) among Taiwanese adults.
Materials and methods
Data source and sample size
We used data from the Taiwan Biobank dataset (2008–2016). The Taiwan Biobank was established to build a data resource consisting of lifestyle and genetic data of a large cohort of Taiwanese adults aged 30 to 70 years. Data collection at Taiwan Biobank recruitment centers is done through questionnaires, biochemical, and physical examinations by well-trained personnel. Each participant signed a consent form prior to the collection of data. Initially, 9553 individuals filled the Taiwan Biobank questionnaires (containing data on alcohol drinking, sex, age, cigarette smoking, coffee/tea intake, exercise, and diet) and underwent both physical (e.g., weight, height, waist-hip ratio, and body fat) and biochemical tests (including genotyping, blood urea nitrogen, creatinine, HDL, LDL, and TG). However, 300 of them were ineligible for the study due to missing information. Hence, 9253 individuals were included in the final analyses. The Institutional Review Board of Cheng Ching General Hospital approved this study (HP200010).
Description of variables
Gout cases were those who self-reported a clinical diagnosis of gout or those who were confirmed by biochemical tests to have serum urate levels ≥ 7 mg/dL (men) or ≥ 6 mg/dL (women). Alcohol drinking was defined as an intake of 150 cc of any alcoholic drink per week continuously for at least 6 months and at the time of data collection. No drinking was defined as drinking less than 150 cc of alcohol per week continuously for at least 6 months. Body mass index, calculated as weight (kg) divided by height squared (m2) was categorized into normal 18.5 ≤ BMI < 24 kg/m2 and abnormal 0 ≤ BMI < 18.5 and BMI ≥24 kg/m2. Waist-hip ratio (WHR), calculated as the ratio of waist to hip circumference was grouped into normal (< 0.9 for men and < 0.85 for women) and abnormal (≥ 0.9 for men and ≥ 0.85 for women). Body fat was classified as normal (< 25 for men and < 30% for women) or abnormal (≥ 25 and ≥ 30% for men and women, respectively). Tea consumption referred to drinking tea at least once per day. Exercise, cigarette smoking, coffee intake, and vegetarian diet were defined as previously elaborated [32–34]. Blood urea nitrogen levels above 20 mg/dL and creatinine levels (≥ 1.4 mg/dL in men and ≥ 1.2 mg/dL in women) were considered abnormal.
Statistical analyses
The SNP (rs671) passed the quality control criteria (Hardy-Weinberg Equilibrium test p-value > 0.001), minor allele frequency ≥ 0.05, and call rate ≥ 95%. Chi-square test was used to estimate differences between categorical variables and the results were presented as n (%). The Student’s t-test was used to estimate differences between continuous variables and the results were presented as mean ± standard deviation (S.D). The interaction between BMI and alcohol drinking and the odds ratios for the association between the dependent (gout) and independent variables (rs671, BMI, alcohol drinking, etc.) were estimated using the multiple logistic regression analysis. In the regression models, we adjusted for covariates, including, sex, age, WHR, body fat, cigarette smoking, coffee intake, tea consumption, exercise, diet, blood urea nitrogen, creatinine, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). We used the dominant model for the SNP data because the enzyme activity in those with the rs671 GG genotype is higher compared to the AG and AA [24]. Moreover, a previous GWAS on gout and rs671 suggested that the dominant model is the model most likely to have higher statistical significance [22]. Data were managed and analyzed using PLINK v1.90 and SAS 9.4 software and the statistical threshold was set at p-value < 0.05 or Bonferroni correction value.
Results
Table 1 presents the demographic features of cases (n = 2352) and non-cases (n = 6901) of gout. Individuals with and without gout were significantly different based on ALDH2 rs671 genotypes (p-value = 0.0122), alcohol drinking (p-value < 0.0001), and BMI (p-value < 0.0001).
Table 1.
Demographic features of cases and non-cases of gout
| Variables | No gout (n = 6901) | Gout (n = 2352) | p-value |
|---|---|---|---|
| Categorical variables | n (%) | n (%) | |
| ALDH2 rs671 genotype | |||
| GG | 3423 (49.60) | 1237 (52.59) | 0.0122 |
| GA+AA | 3478 (50.40) | 1115 (47.41) | |
| Alcohol drinking | |||
| No | 6345 (91.94) | 1966 (83.59) | < 0.0001 |
| Yes | 556 (8.06) | 386 (16.41) | |
| Body mass index | |||
| Normal (≥ 18.5 to <24Kg/m2) | 3790 (54.92) | 665 (28.27) | < 0.0001 |
| Abnormal (< 18.5 and ≥ 24 Kg/m2) | 3111 (45.08) | 1687 (71.73) | |
| Sex | |||
| Women | 4163 (60.32) | 773 (32.87) | < 0.0001 |
| Men | 2738 (39.68) | 1579 (67.13) | |
| Age group (years) | |||
| 30–40 | 1803 (26.13) | 612 (26.02) | 0.0004 |
| 41–50 | 2001 (29.00) | 584 (24.83) | |
| 51–60 | 1944 (28.17) | 718 (30.53) | |
| 61–70 | 1153 (16.71) | 438 (18.62) | |
| Waist-hip ratio | |||
| Normal (men < 0.9; women < 0.85) | 4048 (58.66) | 960 (40.82) | < 0.0001 |
| Abnormal (men ≥ 0.9; women ≥ 0.85) | 2853 (41.34) | 1392 (59.18) | |
| Body fat (%) | |||
| Normal (men < 25; women < 30) | 3953 (57.28) | 987 (41.96) | < 0.0001 |
| Abnormal (men ≥ 25; women ≥ 30) | 2948 (42.72) | 1365 (58.04) | |
| Cigarette smoking status | |||
| Never | 5564 (80.63) | 1607 (68.32) | < 0.0001 |
| Former | 695 (10.07) | 388 (16.50) | |
| Current | 642 (9.30) | 357 (15.18) | |
| Coffee consumption | |||
| No | 4613 (66.85) | 1569 (66.71) | 0.9036 |
| Yes | 2288 (33.15) | 783 (33.29) | |
| Tea consumption | |||
| No | 4506 (65.29) | 1322 (56.21) | < 0.0001 |
| Yes | 2395 (34.71) | 1030 (43.79) | |
| Exercise | |||
| No | 3991 (57.83) | 1370 (58.25) | 0.7241 |
| Yes | 2910 (42.17) | 982 (41.75) | |
| Diet status | |||
| Non-vegetarian | 6208 (89.96) | 2174 (92.43) | < 0.0001 |
| Former vegetarian | 321 (4.65) | 108 (4.59) | |
| Vegan | 372 (5.39) | 70 (2.98) | |
| Blood urea nitrogen (mg/dL) | |||
| Normal (≤ 20) | 6653 (96.41) | 2187 (92.98) | < 0.0001 |
| Abnormal (> 20) | 248 (3.59) | 165 (7.02) | |
| Creatinine (mg/dL) | |||
| Normal (men < 1.4; women < 1.2) | 6885 (99.77) | 2303 (97.92) | < 0.0001 |
| Abnormal (men ≥ 1.4; women ≥ 1.2) | 16 (0.23) | 49 (2.08) | |
| Continuous variables | Mean ± SD | Mean ± SD | |
| HDL-C (mg/dL) | 54.96 ± 13.19 | 47.42 ± 11.17 | < 0.0001 |
| LDL-C (mg/dL) | 118.70 ± 30.91 | 126.30 ± 32.91 | < 0.0001 |
| Triglycerides (mg/dL) | 103.60 ± 75.71 | 155.10 ± 123.10 | < 0.0001 |
n sample size, ALDH2 aldehyde dehydrogenase 2, SD standard deviation, HDL-C high-density lipoprotein cholesterol, LDC-C low-density lipoprotein cholesterol
Table 2 shows the relationship of alcohol drinking, rs671 polymorphism, and BMI with gout. Alcohol drinking (reference, no drinking) and abnormal BMI (reference, normal BMI) were associated with a higher risk of gout while the GA+AA genotype (reference, GG) was associated with a lower risk. The ORs; 95% CIs; p-values were 1.297; 1.098–1.532; 0.0022 for alcohol drinking, 1.550; 1.368–1.755; < 0.0001 for abnormal BMI, and 0.887; 0.0240 for the GA+AA genotype. The interaction between BMI and alcohol on gout was significant (p-value = 0.006). However, the interaction of rs671 with alcohol and BMI was not significant (Table 2).
Table 2.
Association of alcohol drinking, BMI, and ALDH2 rs671 polymorphism with gout
| Variables | OR | 95% CI | p-value |
|---|---|---|---|
| Alcohol drinking (ref, no) | |||
| Yes | 1.297 | 1.098–1.532 | 0.0022 |
| Body mass index (ref, normal) | |||
| Abnormal | 1.550 | 1.368–1.755 | < 0.0001 |
| ALDH2 rs671 genotype (ref, GG) | |||
| GA+AA | 0.887 | 0.800–0.984 | 0.0240 |
| Sex (ref, women) | |||
| Men | 2.363 | 2.068–2.700 | < 0.0001 |
| Age group (ref, 30–40 years) | |||
| 41–50 | 0.710 | 0.614–0.821 | < 0.0001 |
| 51–60 | 0.847 | 0.731–0.981 | 0.0272 |
| 61–70 | 0.871 | 0.733–1.034 | 0.1155 |
| Waist-hip ratio (ref, normal) | |||
| Abnormal | 1.358 | 1.212–1.522 | < 0.0001 |
| Body fat (ref, normal) | |||
| Abnormal | 1.445 | 1.272–1.640 | < 0.0001 |
| Cigarette smoking status (ref, never) | |||
| Former | 0.939 | 0.800–1.102 | 0.4409 |
| Current | 0.791 | 0.667–0.939 | 0.0073 |
| Coffee consumption (ref, no) | |||
| Yes | 1.066 | 0.955–1.190 | 0.2536 |
| Tea consumption (ref, no) | |||
| Yes | 1.223 | 1.099–1.361 | 0.0002 |
| Exercise (ref, no) | |||
| Yes | 1.035 | 0.927–1.157 | 0.5380 |
| Diet status (ref, non-vegetarian) | |||
| Former vegetarian | 1.013 | 0.792–1.296 | 0.9169 |
| Vegan | 0.656 | 0.497–0.867 | 0.0030 |
| Blood urea nitrogen (ref, normal) | |||
| Abnormal | 1.420 | 1.118–1.803 | 0.0041 |
| Creatinine (ref, normal) | |||
| Abnormal | 5.320 | 2.846–9.945 | < 0.0001 |
| HDL-C | 0.980 | 0.975–0.985 | < 0.0001 |
| LDL-C | 1.006 | 1.005–1.008 | < 0.0001 |
| Triglycerides | 1.003 | 1.002–1.004 | < 0.0001 |
Interaction between BMI and alcohol drinking (p-value = 0.0006)
BMI body mass index, OR odds ratio, CI confidence interval, ref reference, ALDH2 aldehyde dehydrogenase 2, HDL-C high-density lipoprotein cholesterol, LDC-C low-density lipoprotein cholesterol
Table 3 shows the association of alcohol drinking and BMI with gout stratified by rs671 genotypes (GG and GA+AA). Both BMI and alcohol drinking were associated with a higher risk of gout. For alcohol, the association was significant in only the GG category (OR = 1.289; 95% CI = 1.048–1.586; p-value = 0.162). However, for BMI, the association was significant in both the GG (OR = 1.584; 95% CI = 1.332–1.883; p-value < 0.0001) and GA+AA (OR = 1.518; 95% CI = 1.268–1.818; p-value < 0.0001) categories. The interaction between BMI and alcohol on gout was significant for both GG (p-value = 0.0102) and GA+AA (p-value = 0.0175).
Table 3.
Association of alcohol drinking and BMI with gout stratified by ALDH2 rs671 genotypes
| Variables | GG (n = 4660) | GA+AA (n = 4593) | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Alcohol drinking (ref, no) | ||||||
| Yes | 1.289 | 1.048–1.586 | 0.0162 | 1.273 | 0.950–1.706 | 0.1062 |
| Body mass index (ref, normal) | ||||||
| Abnormal | 1.584 | 1.332–1.883 | < 0.0001 | 1.518 | 1.268–1.818 | < 0.0001 |
| Sex (ref, women) | ||||||
| Men | 2.322 | 1.924–2.802 | < 0.0001 | 2.378 | 1.966–2.876 | < 0.0001 |
| Age group (ref, 30–40 years) | ||||||
| 41–50 | 0.633 | 0.516–0.776 | < 0.0001 | 0.800 | 0.649–0.986 | 0.0362 |
| 51–60 | 0.798 | 0.649–0.981 | 0.0318 | 0.899 | 0.727–1.111 | 0.0248 |
| 61–70 | 0.917 | 0.722–1.164 | 0.4750 | 0.821 | 0.640–1.054 | 0.1215 |
| Waist-hip ratio (ref, normal) | ||||||
| Abnormal | 1.301 | 1.109–1.526 | 0.0012 | 1.419 | 1.205–1.670 | < 0.0001 |
| Body fat (ref, normal) | ||||||
| Abnormal | 1.469 | 1.230–1.755 | < 0.0001 | 1.414 | 1.178–1.698 | 0.0002 |
| Cigarette smoking status (ref, never) | ||||||
| Former | 1.081 | 0.865–1.351 | 0.4948 | 0.811 | 0.644–1.023 | 0.0769 |
| Current | 0.916 | 0.720–1.165 | 0.4745 | 0.698 | 0.546–0.892 | 0.0041 |
| Coffee consumption (ref, no) | ||||||
| Yes | 1.142 | 0.981–1.329 | 0.0878 | 0.991 | 0.845–1.163 | 0.9141 |
| Tea consumption (ref, no) | ||||||
| Yes | 1.195 | 1.029–1.388 | 0.0197 | 1.263 | 1.084–1.472 | 0.0028 |
| Exercise (ref, no) | ||||||
| Yes | 0.996 | 0.854–1.162 | 0.9594 | 1.084 | 0.924–1.272 | 0.3232 |
| Diet status (ref, non-vegetarian) | ||||||
| Former vegetarian | 1.172 | 0.828–1.660 | 0.3704 | 0.869 | 0.612–1.234 | 0.4317 |
| Vegan | 0.647 | 0.437–0.959 | 0.0299 | 0.657 | 0.443–0.975 | 0.0370 |
| Blood urea nitrogen (ref, normal) | ||||||
| Abnormal | 1.268 | 0.900–1.786 | 0.1744 | 1.558 | 1.113–2.182 | 0.0098 |
| Creatinine (ref, normal) | ||||||
| Abnormal | 6.216 | 2.738–14.111 | < 0.0001 | 4.418 | 1.630–11.972 | 0.0035 |
| HDL-C | 0.981 | 0.974–0.988 | < 0.0001 | 0.979 | 0.971–0.987 | < 0.0001 |
| LDL-C | 1.007 | 1.005–1.009 | < 0.0001 | 1.006 | 1.003–1.008 | < 0.0001 |
| Triglycerides | 1.003 | 1.002–1.004 | < 0.0001 | 1.003 | 1.002–1.004 | < 0.0001 |
Interaction between BMI and alcohol drinking (p-value = 0.0102 and 0.0175 for the GG and GA+AA group, respectively)
BMI body mass index, OR odds ratio, CI confidence interval, ref reference, ALDH2 Aldehyde dehydrogenase 2, HDL-C high-density lipoprotein cholesterol, LDC-C low-density lipoprotein cholesterol
Tables 4 and 5 illustrate the association between alcohol drinking and gout among participants with ALDH2 rs671 GG and GA+AA stratified by BMI. Alcohol drinking was significantly associated with gout only among individuals with a normal BMI. This results were observed for both GG: OR; 95% CI; p-value = 1.533; 1.036–2.269; 0.0325 (Table 4) and GA+AA: OR; 95% CI; p-value = 2.109; 1.202–3.699; 0.0092 (Table 5).
Table 4.
Association between alcohol drinking and gout among participants with the ALDH2 rs671 GG genotype stratified by BMI
| Variables | GG genotype (n = 4660) | |||||
|---|---|---|---|---|---|---|
| Normal (n = 2239) | Abnormal (n = 2421) | |||||
| OR | 95% CI | P-value | OR | 95% CI | P-value | |
| Alcohol drinking (ref: no) | ||||||
| yes | 1.533 | 1.036-2.269 | 0.0325 | 1.205 | 0.945-1.538 | 0.1331 |
| Sex (ref: women) | ||||||
| men | 2.742 | 1.996-3.765 | <0.0001 | 2.116 | 1.671-2.681 | <0.0001 |
| Age group (ref: 30-40 years) | ||||||
| 41-50 | 0.711 | 0.492-1.028 | 0.0697 | 0.578 | 0.450-0.742 | <0.0001 |
| 51-60 | 1.064 | 0.740-1.531 | 0.7370 | 0.638 | 0.495-0.823 | 0.0005 |
| 61-70 | 0.906 | 0.591-1.391 | 0.6533 | 0.850 | 0.634-1.141 | 0.2792 |
| Waist-hip ratio (ref: normal) | ||||||
| abnormal | 1.647 | 1.246-2.177 | 0.0005 | 1.166 | 0.959-1.418 | 0.1236 |
| Body fat (ref: normal) | ||||||
| abnormal | 1.244 | 0.900-1.718 | 0.1861 | 1.595 | 1.282-1.985 | <0.0001 |
| Cigarette smoking status (ref: never) | ||||||
| former | 1.098 | 0.720-1.675 | 0.6640 | 1.121 | 0.861-1.459 | 0.3961 |
| current | 1.032 | 0.666-1.600 | 0.8881 | 0.839 | 0.629-1.120 | 0.2344 |
| Coffee consumption (ref: no) | ||||||
| yes | 1.235 | 0.946-1.611 | 0.1207 | 1.112 | 0.922-1.341 | 0.2660 |
| Tea consumption (ref: no) | ||||||
| yes | 1.237 | 0.946-1.618 | 0.1204 | 1.181 | 0.985-1.416 | 0.0721 |
| Exercise (ref: no) | ||||||
| yes | 1.303 | 0.995-1.706 | 0.0545 | 0.860 | 0.712-1.039 | 0.1180 |
| Diet status (ref: non-vegetarian) | ||||||
| former vegetarian | 0.770 | 0.386-1.539 | 0.4603 | 1.480 | 0.966-2.268 | 0.0716 |
| vegan | 0.689 | 0.383-1.238 | 0.2124 | 0.554 | 0.323-0.950 | 0.0318 |
| Blood urea nitrogen (ref: normal) | ||||||
| abnormal | 0.865 | 0.441-1.694 | 0.6721 | 1.544 | 1.028-2.319 | 0.0363 |
| Creatinine (ref: normal) | ||||||
| abnormal | 19.851 | 3.691-106.761 | 0.0005 | 3.885 | 1.542-9.790 | 0.0040 |
| HDL-C | 0.980 | 0.969-0.991 | 0.0006 | 0.981 | 0.973-0.990 | <0.0001 |
| LDL-C | 1.010 | 1.006-1.014 | <0.0001 | 1.005 | 1.002-1.008 | 0.0004 |
| Triglycerides | 1.004 | 1.002-1.006 | <0.0001 | 1.002 | 1.001-1.003 | <0.0001 |
BMI body mass index, OR odds ratio, ref reference, ALDH2 aldehyde dehydrogenase 2, HDL-C high density lipoprotein cholesterol, LDC-C low density lipoprotein cholesterol
Table 5.
Association between alcohol drinking and gout among participants with the ALDH2 rs671 GA+AA genotype stratified by BMI
| Variables | GA+AA genotype (n = 4593) | |||||
|---|---|---|---|---|---|---|
| Normal (n = 2216) | Abnormal (n = 2377) | |||||
| OR | 95% CI | p-value | OR | 95% CI | p-value | |
| Alcohol drinking (ref, no) | ||||||
| Yes | 2.109 | 1.202–3.699 | 0.0092 | 1.108 | 0.789–1.557 | 0.5525 |
| Sex (ref, women) | ||||||
| Men | 2.561 | 1.854–3.539 | < 0.0001 | 2.190 | 1.724–2.780 | < 0.0001 |
| Age group (ref, 30–40 years) | ||||||
| 41–50 | 1.119 | 0.766–1.635 | 0.5601 | 0.664 | 0.514–0.857 | 0.0017 |
| 51–60 | 1.329 | 0.905–1.951 | 0.1469 | 0.743 | 0.572–0.965 | 0.0260 |
| 61–70 | 1.536 | 0.991–2.382 | 0.0552 | 0.589 | 0.433–0.803 | 0.0008 |
| Waist-hip ratio (ref, normal) | ||||||
| Abnormal | 1.410 | 1.063–1.869 | 0.0171 | 1.441 | 1.176–1.766 | 0.0004 |
| Body fat (ref, normal) | ||||||
| Abnormal | 1.331 | 0.955–1.856 | 0.0913 | 1.392 | 1.113–1.742 | 0.0038 |
| Cigarette smoking status (ref, never) | ||||||
| Former | 0.527 | 0.326–0.851 | 0.0088 | 0.950 | 0.725–1.243 | 0.7065 |
| Current | 0.890 | 0.580–1.365 | 0.5936 | 0.591 | 0.438–0.798 | 0.0006 |
| Coffee consumption (ref, no) | ||||||
| Yes | 0.955 | 0.720–1.268 | 0.7516 | 0.996 | 0.820–1.211 | 0.9712 |
| Tea consumption (ref, no) | ||||||
| Yes | 1.562 | 1.193–2.046 | 0.0012 | 1.150 | 0.953–1.387 | 0.1454 |
| Exercise (ref, no) | ||||||
| Yes | 1.155 | 0.873–1.527 | 0.3127 | 1.024 | 0.841–1.248 | 0.8108 |
| Diet status (ref, non-vegetarian) | ||||||
| Former vegetarian | 0.443 | 0.200–0.979 | 0.0442 | 1.090 | 0.721–1.650 | 0.6821 |
| Vegan | 0.492 | 0.247–0.980 | 0.0437 | 0.765 | 0.466–1.254 | 0.2876 |
| Blood urea nitrogen (ref, normal) | ||||||
| Abnormal | 2.231 | 1.313–3.791 | 0.0030 | 1.217 | 0.792–1.871 | 0.3696 |
| Creatinine (ref, normal) | ||||||
| Abnormal | 1.715 | 0.407–7.234 | 0.4626 | 10.705 | 2.082–55.046 | 0.0045 |
| HDL-C | 0.979 | 0.967–0.991 | 0.0007 | 0.979 | 0.969–0.989 | < 0.0001 |
| LDL-C | 1.006 | 1.002–1.010 | 0.0053 | 1.006 | 1.003–1.009 | 0.0002 |
| Triglycerides | 1.004 | 1.002–1.005 | < 0.0001 | 1.003 | 1.002–1.004 | < 0.0001 |
BMI body mass index, OR odds ratio, CI confidence interval, ref reference, ALDH2 aldehyde dehydrogenase 2, HDL-C high-density lipoprotein cholesterol, LDC-C low-density lipoprotein cholesterol
Table 6 shows the risk of gout in relation to the combination of BMI and alcohol drinking among participants stratified by ALDH2 rs671 genotypes. Compared to the reference category (no alcohol drinking and normal BMI), the risk of gout was significantly higher for both GG and GA+AA. For the GG category, the ORs (95% CI; p-value) were 1.851 (1.316–2.603; 0.0004) for normal BMI and alcohol drinking, 1.727 (1.433–2.080; < 0.0001) for abnormal BMI and no alcohol drinking, and 1.913 (1.451–2.523; < 0.0001) for abnormal BMI and alcohol drinking. For the GA+AA category, the OR (95% CI; p-value) were 2.212 (1.302–3.757; 0.0033) for normal BMI and alcohol drinking, 1.592 (1.323–1.916; < 0.0001) for abnormal BMI and no alcohol drinking, and 1.675 (1.166–2.407; 0.0053) for abnormal BMI and alcohol drinking.
Table 6.
Risk of gout in relation to the combination of BMI and alcohol drinking among participants stratified by ALDH2 rs671 genotypes
| Variables | GG (n = 4660) | GA+AA (n = 4593) | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | p-value | OR | 95% CI | p-value | |
| BMI and alcohol drinking (ref, normal BMI and no alcohol drinking) | ||||||
| Normal BMI and alcohol drinking | 1.851 | 1.316–2.603 | 0.0004 | 2.212 | 1.302–3.757 | 0.0033 |
| Abnormal BMI and no alcohol drinking | 1.727 | 1.433–2.080 | < 0.0001 | 1.592 | 1.323–1.916 | < 0.0001 |
| Abnormal BMI and alcohol drinking | 1.913 | 1.451–2.523 | < 0.0001 | 1.675 | 1.166–2.407 | 0.0053 |
| Sex (ref, women) | ||||||
| Men | 2.312 | 1.915–2.790 | < 0.0001 | 2.377 | 1.965–2.876 | < 0.0001 |
| Age group (ref, 30–40 years) | ||||||
| 41–50 | 0.633 | 0.516–0.777 | < 0.0001 | 0.798 | 0.648–0.983 | 0.0343 |
| 51–60 | 0.798 | 0.649–0.981 | 0.0320 | 0.904 | 0.731–1.118 | 0.3501 |
| 61–70 | 0.914 | 0.720–1.161 | 0.4632 | 0.820 | 0.639–1.052 | 0.1189 |
| Waist-hip ratio (ref, normal) | ||||||
| Abnormal | 1.304 | 1.111–1.529 | 0.0011 | 1.426 | 1.211–1.679 | < 0.0001 |
| Body fat (ref, normal) | ||||||
| Abnormal | 1.479 | 1.237–1.767 | < 0.0001 | 1.415 | 1.178–1.699 | 0.0002 |
| Cigarette smoking status (ref, never) | ||||||
| Former | 1.078 | 0.863–1.347 | 0.5082 | 0.810 | 0.643–1.021 | 0.0745 |
| Current | 0.903 | 0.710–1.149 | 0.4079 | 0.692 | 0.541–0.884 | 0.0033 |
| Coffee consumption (ref, no) | ||||||
| Yes | 1.131 | 0.971–1.317 | 0.1130 | 0.984 | 0.839–1.155 | 0.8477 |
| Tea consumption (ref, no) | ||||||
| Yes | 1.192 | 1.026–1.384 | 0.0215 | 1.266 | 1.086–1.476 | 0.0026 |
| Exercise (ref, no) | ||||||
| Yes | 1.001 | 0.858–1.168 | 0.9904 | 1.084 | 0.924–1.272 | 0.3235 |
| Diet status (ref, non-vegetarian) | ||||||
| Former vegetarian | 1.155 | 0.815–1.636 | 0.4186 | 0.869 | 0.612–1.234 | 0.4333 |
| Vegan | 0.641 | 0.433–0.950 | 0.0267 | 0.663 | 0.447–0.985 | 0.0417 |
| Blood urea nitrogen (ref, normal) | ||||||
| Abnormal | 1.279 | 0.909–1.801 | 0.1576 | 1.561 | 1.114–2.187 | 0.0097 |
| Creatinine (ref, normal) | ||||||
| Abnormal | 6.192 | 2.726–14.067 | < 0.0001 | 4.449 | 1.639–12.076 | 0.0034 |
| HDL-C | 0.980 | 0.973–0.987 | < 0.0001 | 0.979 | 0.972–0.987 | < 0.0001 |
| LDL-C | 1.007 | 1.005–1.009 | < 0.0001 | 1.006 | 1.003–1.008 | < 0.0001 |
| Triglycerides | 1.003 | 1.002–1.004 | < 0.0001 | 1.003 | 1.002–1.004 | < 0.0001 |
BMI body mass index, OR odds ratio, CI confidence interval, ref reference, ALDH2 Aldehyde dehydrogenase 2, HDL-C high-density lipoprotein cholesterol, LDC-C low-density lipoprotein cholesterol
Table 7 displays the risk of gout in relation to the combination of BMI and alcohol drinking among participants stratified by ALDH2 rs671 genotypes. Compared to the reference category (GG genotype, normal BMI, and no alcohol drinking), the risk of gout was significantly higher for all but one category (GA+AA, normal BMI, and no alcohol drinking). The OR (95% CI; p-value) was 1.929 (1.385–2.688; 0.0001) for GG, normal BMI, and alcohol drinking; 1.721 (1.442–2.052; < 0.0001) for GG, abnormal BMI, and no alcohol drinking; 1.941 (1.501–2.511; < 0.0001) for GG, abnormal BMI, and alcohol drinking; 0.937 (0.779–1.126; 0.4862) for GA+AA, normal BMI, and no alcohol drinking; 1.971 (1.167–3.327; 0.0111) for GA+AA, normal BMI, and alcohol drinking; 1.498 (1.1256–1.786; < 0.0001) for GA+AA, abnormal BMI, and no alcohol drinking; and 1.545 (1.088–2.194; 0.0150) for GA+AA, abnormal BMI, and alcohol drinking. Some covariates that were consistently associated with gout (Tables 2, 3, 4, 5, 6, and 7) included sex (high risk in men compared to women), HDL-C (lower risk), LDL-C (higher risk), and TG (higher risk).
Table 7.
Risk of gout in relation to the combination of BMI, alcohol drinking, and ALDH2 rs671 polymorphism
| Variables | OR | 95% CI | p-value |
|---|---|---|---|
| ALDH2 rs671 genotypes, BMI, and alcohol drinking (ref, GG, normal BMI, no alcohol drinking) | |||
| GG, normal BMI, and alcohol drinking | 1.929 | 1.385–2.688 | 0.0001 |
| GG, abnormal BMI, and no alcohol drinking | 1.721 | 1.442–2.052 | < 0.0001 |
| GG, abnormal BMI, and alcohol drinking | 1.941 | 1.501–2.511 | < 0.0001 |
| GA+AA, normal BMI, and no alcohol drinking | 0.937 | 0.779–1.126 | 0.4862 |
| GA+AA, normal BMI, and alcohol drinking | 1.971 | 1.167–3.327 | 0.0111 |
| GA+AA, abnormal BMI, and no alcohol drinking | 1.498 | 1.256–1.786 | < 0.0001 |
| GA+AA, abnormal BMI, and alcohol drinking | 1.545 | 1.088–2.194 | 0.0150 |
| Sex (ref, women) | |||
| Men | 2.355 | 2.061–2.692 | < 0.0001 |
| Age group (ref, 30–40 years) | |||
| 41–50 | 0.709 | 0.613–0.820 | < 0.0001 |
| 51–60 | 0.849 | 0.732–0.984 | 0.0297 |
| 61–70 | 0.869 | 0.731–1.032 | 0.1083 |
| Waist-hip ratio (ref, normal) | |||
| Abnormal | 1.362 | 1.216–1.527 | < 0.0001 |
| Body fat (ref, normal) | |||
| Abnormal | 1.450 | 1.276–1.647 | < 0.0001 |
| Cigarette smoking status (ref, never) | |||
| Former | 0.937 | 0.799–1.100 | 0.4268 |
| Current | 0.782 | 0.659–0.928 | 0.0049 |
| Coffee consumption (ref, no) | |||
| Yes | 1.058 | 0.948–1.180 | 0.3177 |
| Tea consumption (ref, no) | |||
| Yes | 1.223 | 1.099–1.360 | 0.0002 |
| Exercise (ref, no) | |||
| Yes | 1.039 | 0.930–1.160 | 0.5007 |
| Diet status (ref, non-vegetarian) | |||
| Former vegetarian | 1.006 | 0.787–1.286 | 0.9623 |
| Vegan | 0.656 | 0.497–0.867 | 0.0030 |
| Blood urea nitrogen (ref, normal) | |||
| Abnormal | 1.426 | 1.123–1.812 | 0.0036 |
| Creatinine (ref, normal) | |||
| Abnormal | 5.324 | 2.845–9.962 | < 0.0001 |
| HDL-C | 0.980 | 0.975–0.985 | < 0.0001 |
| LDL-C | 1.006 | 1.005–1.008 | < 0.0001 |
| Triglycerides | 1.003 | 1.002–1.004 | < 0.0001 |
BMI body mass index, OR odds ratio, CI confidence interval, ref reference, ALDH2 Aldehyde dehydrogenase 2, HDL-C high-density lipoprotein cholesterol, LDC-C low-density lipoprotein cholesterol
Discussion
In the present study, the rs671 GA+AA genotype was associated with a lower risk of gout, while alcohol and abnormal BMI were associated with a higher risk. Of note, BMI and alcohol had a significant interaction on gout risk among individuals with GG and GA+AA. However, there was no significant interaction of rs671 with either BMI or alcohol drinking. Stratified analyses revealed that alcohol drinking especially among normal-weight individuals could confer susceptibility to gout, irrespective of genotype. These findings confirm the major role of alcohol consumption in the risk of gout. However, we cannot state the precise underlying biological mechanisms. Similar to our results, significant interactions between BMI and alcohol on hyperuricemia have been documented [17, 35]. Based on their findings, Shiraishi and Une advised obese people to reduce the amount of alcohol they consume [35].
Many past studies reported significant associations between gout and rs671 [22, 29, 30, 36]. This variant was described as a real gout-SNP [22, 29, 30]. The A allele of the rs671 has been linked to reduced susceptibility to gout [22]. ALDH2 rs671 also demonstrated the strongest GWA significance for alcohol drinking [21]. It was found to be related to alcohol drinking habits and alcohol flushing responses in Asians [25, 37]. Rapid metabolism of acetaldehyde and ethanol associated with a homozygous ALDH2 rs671 genotype was linked to higher levels of UA in Japanese alcoholic men [26]. The relationship between gout and rs671 could in part be accounted for by alcohol drinking [22].
Previous studies on the risk of gout based on alcohol consumption showed conflicting findings. Most pioneer epidemiological research reported no association, probably because of a relatively small number of gout cases and failure to adjust for vital confounders [38–40]. Nonetheless, subsequent studies with higher gout cases showed significant associations [13, 16]. A potential explanatory mechanism implicated in the relationship between gout and alcohol is that it enhances uric acid production and the hepatic breakdown of adenosine triphosphate (ATP) [41]. Moreover, alcoholic drinks like beer are rich in purine, which is associated with high levels of uric acid [42].
Evidence from a study using the UK biobank data suggested that genetic polymorphisms have a strong effect on gout regardless of BMI [43]. ALDH2 rs671 attained a significant genome-wide association for BMI [31] and was reported as the only locus having a significant independent association with BMI [31]. Numerous prospective studies on Asians, Europeans, and Americans suggested that BMI is positively related to the odds of gout and this relationship is possibly mediated by several factors [8, 9, 39, 43–52]. However, there were also reports of no significant relationship between BMI and gout [40]. The role of BMI in gout pathogenesis could be elucidated based on how leptin responds to inflammation related to monosodium urate crystals [53, 54]. BMI could also cause gout through its effect on serum urate [52, 55], potentially through insulinemia which affects renal reabsorption and uric acid clearance [56–59].
Previous studies also had similar findings on the risk of gout pertaining to sex, cigarette smoking, lipoproteins, and other variables [6, 7, 60, 61].
The current study is limited in that the gout population in this study may not be representative of gout patients in the general population. This is because about 33% of gout cases were women. This percentage appears high given that the prevalence of gout in Taiwanese men is about 4 times higher than that in women. Moreover, we defined cases as those who self-reported a clinical diagnosis of gout or those with uric acid levels ≥ 7 mg/dL (men) or ≥ 6 mg/dL (women). However, there was no information regarding patients on effective ULT and so the results are possibly not generalizable. In addition, the cohort is 25% gout cases and is thus closer to a case-control cohort than a general population sample. Another limitation of our study is that we could not clearly explain the precise biological mechanisms underlying the reported relationships.
Conclusion
Alcohol and abnormal BMI were associated with a higher risk of gout, while the rs671 GA+AA genotype was associated with a lower risk. Of note, BMI and alcohol had a significant interaction on gout risk among individuals with GG and GA+AA. Stratified analyses revealed that alcohol drinking, especially among normal-weight individuals confers a great risk of gout irrespective of genotype. These findings confirm the major role of alcohol consumption on gout and so both normal weight and abnormal weight individuals are advised to reduce the amount of alcohol they consume. Reducing the amount of alcohol intake could play a great role in public health as it might mitigate the risk of gout.
Acknowledgements
Not applicable.
Abbreviations
- BMI
Body mass index
- OR
Odds ratio
- ref
Reference
- ALDH2
Aldehyde dehydrogenase 2
- HDL-C
High-density lipoprotein cholesterol
- LDC-C
Low-density lipoprotein cholesterol
Authors’ contributions
Conceptualization, Y-R L, DMT, C-C L, C-HH, and Y-PL. Formal analysis, C-HH and Y-PL. Methodology, Y-R L, DMT, C-C L, C-HH, and Y-PL. Supervision, Y-PL. Validation, Y-R L, DMT, C-C L, C-HH, and Y-PL. Writing—original draft, Y-R L and DMT. Writing—review and editing, Y-R L, DMT, C-C L, C-HH, and Y-PL. The authors read and approved the final manuscript.
Funding
This project was funded by grants from the Cheng Ching General Hospital, Chung Kang branch (CH10900247A) and in part by the Ministry of Science and Technology, Taiwan (MOST 108-2621-M-040-001).
Availability of data and materials
The data that support the findings of this study are available from Taiwan Biobank but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are however available from Professor Yung Po Liaw (email address, Liawyp@csmu.edu.tw; tel, + 886424730022 ext. 12102) upon reasonable request and with permission of Taiwan Biobank.
Declarations
Ethics approval and consent to participate
Each participant signed an informed consent form. The Institutional Review Board of Cheng Ching General Hospital approved this study (HP200010).
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Jeong H, Jeon CH. Clinical characteristics and risk factors for gout flare during the postsurgical period. Adv Rheumatol. 2019;59(1):31. doi: 10.1186/s42358-019-0075-7. [DOI] [PubMed] [Google Scholar]
- 2.Lin K-C, Lin H, Chou P. The interaction between uric acid level and other risk factors on the development of gout among asymptomatic hyperuricemic men in a prospective study. J Rheumatol. 2000;27(6):1501–1505. [PubMed] [Google Scholar]
- 3.Dehlin M, Jacobsson L, Roddy E. Global epidemiology of gout: prevalence, incidence, treatment patterns and risk factors. Nat Rev Rheumatol. 2020;16(7):380–390. doi: 10.1038/s41584-020-0441-1. [DOI] [PubMed] [Google Scholar]
- 4.Kuo C-F, Grainge MJ, See L-C, Yu K-H, Luo S-F, Zhang W, Doherty M. Epidemiology and management of gout in Taiwan: a nationwide population study. Arthritis Res Ther. 2015;17(1):13. doi: 10.1186/s13075-015-0522-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Chuang S-Y, Lee S-C, Hsieh Y-T, Pan W-H. Trends in hyperuricemia and gout prevalence: Nutrition and Health Survey in Taiwan from 1993-1996 to 2005-2008. Asia Pac J Clin Nutr. 2011;20(2):301–308. [PubMed] [Google Scholar]
- 6.Wang W, Krishnan E. Cigarette smoking is associated with a reduction in the risk of incident gout: results from the Framingham Heart Study original cohort. Rheumatology. 2015;54(1):91–95. doi: 10.1093/rheumatology/keu304. [DOI] [PubMed] [Google Scholar]
- 7.Singh JA, Gaffo A. Gout epidemiology and comorbidities. WB Saunders: In Seminars in Arthritis and Rheumatism; 2020:50(3):S11–S16. [DOI] [PubMed]
- 8.Bhole V, de Vera M, Rahman MM, Krishnan E, Choi H. Epidemiology of gout in women: fifty-two–year followup of a prospective cohort. Arthritis Rheum. 2010;62(4):1069–1076. doi: 10.1002/art.27338. [DOI] [PubMed] [Google Scholar]
- 9.Roddy E, Doherty M. Gout. Epidemiology of gout. Arthritis Res Ther. 2010;12(6):223. doi: 10.1186/ar3199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Singh JA, Reddy SG, Kundukulam J. Risk factors for gout and prevention: a systematic review of the literature. Curr Opin Rheumatol. 2011;23(2):192–202. doi: 10.1097/BOR.0b013e3283438e13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Lyu L-C, Hsu C-Y, Yeh C-Y, Lee M-S, Huang S-H, Chen C-L. A case-control study of the association of diet and obesity with gout in Taiwan. Am J Clin Nutr. 2003;78(4):690–701. doi: 10.1093/ajcn/78.4.690. [DOI] [PubMed] [Google Scholar]
- 12.Zhou H, Ma ZF, Lu Y, Du Y, Shao J, Wang L, et al. Elevated serum uric acid, hyperuricaemia and dietary patterns among adolescents in mainland China. J Pediatr Endocrinol Metab. 2020;1 ahead-of-print [DOI] [PubMed]
- 13.Choi HK, Atkinson K, Karlson EW, Willett W, Curhan G. Alcohol intake and risk of incident gout in men: a prospective study. Lancet. 2004;363(9417):1277–1281. doi: 10.1016/S0140-6736(04)16000-5. [DOI] [PubMed] [Google Scholar]
- 14.Gao B, Zhou J, Ge J, Zhang Y, Chen F, Lau WB, Wan Y, Zhang N, Xing Y, Wang L, Fu J, Li X, Jia H, Zhao X, Ji Q. Association of maximum weight with hyperuricemia risk: a retrospective study of 21,414 Chinese people. PLoS One. 2012;7(11):e51186. doi: 10.1371/journal.pone.0051186. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Lyngdoh T, Vuistiner P, Marques-Vidal P, Rousson V, Waeber G, Vollenweider P, Bochud M. Serum uric acid and adiposity: deciphering causality using a bidirectional Mendelian randomization approach. PLoS One. 2012;7(6):e39321. doi: 10.1371/journal.pone.0039321. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Zhang Y, Woods R, Chaisson CE, Neogi T, Niu J, McAlindon TE, et al. Alcohol consumption as a trigger of recurrent gout attacks. Am J Med. 2006;119(9):800. e11–800. e16. doi: 10.1016/j.amjmed.2006.01.020. [DOI] [PubMed] [Google Scholar]
- 17.Choi HK, Curhan G. Beer, liquor, and wine consumption and serum uric acid level: the third National Health and Nutrition Examination Survey. Arthritis Care Res. 2004;51(6):1023–1029. doi: 10.1002/art.20821. [DOI] [PubMed] [Google Scholar]
- 18.Yamamoto T, Moriwaki Y, Takahashi S. Effect of ethanol on metabolism of purine bases (hypoxanthine, xanthine, and uric acid) Clin Chim Acta. 2005;356(1–2):35–57. doi: 10.1016/j.cccn.2005.01.024. [DOI] [PubMed] [Google Scholar]
- 19.Zhang D, Yang M, Zhou D, Li Z, Cai L, Bao Y, Li H, Shan Z, Liu J, Lv D, Liu Y, Xu C, Ling J, Xu Y, Zhang S, Huang Q, Shi Y, Zhu Y, Lai M. The polymorphism rs671 at ALDH2 associated with serum uric acid levels in Chinese Han males: a genome-wide association study. Gene. 2018;651:62–69. doi: 10.1016/j.gene.2018.01.064. [DOI] [PubMed] [Google Scholar]
- 20.Jee YH, Jung KJ, Park YB, Spiller W, Jee SH. Causal effect of alcohol consumption on hyperuricemia using a Mendelian randomization design. Int J Rheum Dis. 2019;22(10):1912–1919. doi: 10.1111/1756-185X.13668. [DOI] [PubMed] [Google Scholar]
- 21.Nakayama A, Nakatochi M, Kawamura Y, Yamamoto K, Nakaoka H, Shimizu S, Higashino T, Koyama T, Hishida A, Kuriki K, Watanabe M, Shimizu T, Ooyama K, Ooyama H, Nagase M, Hidaka Y, Matsui D, Tamura T, Nishiyama T, Shimanoe C, Katsuura-Kamano S, Takashima N, Shirai Y, Kawaguchi M, Takao M, Sugiyama R, Takada Y, Nakamura T, Nakashima H, Tsunoda M, Danjoh I, Hozawa A, Hosomichi K, Toyoda Y, Kubota Y, Takada T, Suzuki H, Stiburkova B, Major TJ, Merriman TR, Kuriyama N, Mikami H, Takezaki T, Matsuo K, Suzuki S, Hosoya T, Kamatani Y, Kubo M, Ichida K, Wakai K, Inoue I, Okada Y, Shinomiya N, Matsuo H, Japan Gout Genomics Consortium (Japan Gout) Subtype-specific gout susceptibility loci and enrichment of selection pressure on ABCG2 and ALDH2 identified by subtype genome-wide meta-analyses of clinically defined gout patients. Ann Rheum Dis. 2020;79(5):657–665. doi: 10.1136/annrheumdis-2019-216644. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Sakiyama M, Matsuo H, Nakaoka H, Yamamoto K, Nakayama A, Nakamura T, Kawai S, Okada R, Ooyama H, Shimizu T, Shinomiya N. Identification of rs671, a common variant of ALDH2, as a gout susceptibility locus. Sci Rep. 2016;6(1):25360. doi: 10.1038/srep25360. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Cui R, Kamatani Y, Takahashi A, Usami M, Hosono N, Kawaguchi T, Tsunoda T, Kamatani N, Kubo M, Nakamura Y, Matsuda K. Functional variants in ADH1B and ALDH2 coupled with alcohol and smoking synergistically enhance esophageal cancer risk. Gastroenterology. 2009;137(5):1768–1775. doi: 10.1053/j.gastro.2009.07.070. [DOI] [PubMed] [Google Scholar]
- 24.Matsuo K, Wakai K, Hirose K, Ito H, Saito T, Tajima K. Alcohol dehydrogenase 2 His47Arg polymorphism influences drinking habit independently of aldehyde dehydrogenase 2 Glu487Lys polymorphism: analysis of 2,299 Japanese subjects. Cancer Epidemiol Prev Biomarkers. 2006;15(5):1009–1013. doi: 10.1158/1055-9965.EPI-05-0911. [DOI] [PubMed] [Google Scholar]
- 25.Takeuchi F, Isono M, Nabika T, Katsuya T, Sugiyama T, Yamaguchi S, Kobayashi S, Ogihara T, Yamori Y, Fujioka A, Kato N. Confirmation of ALDH2 as a major locus of drinking behavior and of its variants regulating multiple metabolic phenotypes in a Japanese population. Circ J. 2011;75(4):911–918. doi: 10.1253/circj.CJ-10-0774. [DOI] [PubMed] [Google Scholar]
- 26.Yokoyama A, Yokoyama T, Mizukami T, Matsui T, Kimura M, Matsushita S, Higuchi S, Maruyama K. Alcohol dehydrogenase-1B (rs1229984) and aldehyde dehydrogenase-2 (rs671) genotypes and alcoholic ketosis are associated with the serum uric acid level in Japanese alcoholic men. Alcohol Alcohol. 2016;51(3):268–274. doi: 10.1093/alcalc/agv123. [DOI] [PubMed] [Google Scholar]
- 27.Yokoyama A, Tsutsumi E, Imazeki H, Suwa Y, Nakamura C, Yokoyama T. Polymorphisms of alcohol dehydrogenase-1B and aldehyde dehydrogenase-2 and the blood and salivary ethanol and acetaldehyde concentrations of Japanese alcoholic men. Alcohol Clin Exp Res. 2010;34(7):1246–1256. doi: 10.1111/j.1530-0277.2010.01202.x. [DOI] [PubMed] [Google Scholar]
- 28.Yokoyama A, Mizukami T, Matsui T, Yokoyama T, Kimura M, Matsushita S, Higuchi S, Maruyama K. Genetic polymorphisms of alcohol dehydrogenase-1 B and aldehyde dehydrogenase-2 and liver cirrhosis, chronic calcific pancreatitis, diabetes mellitus, and hypertension among Japanese alcoholic men. Alcohol Clin Exp Res. 2013;37(8):1391–1401. doi: 10.1111/acer.12108. [DOI] [PubMed] [Google Scholar]
- 29.Kawamura Y, Nakaoka H, Nakayama A, Okada Y, Yamamoto K, Higashino T, Sakiyama M, Shimizu T, Ooyama H, Ooyama K, Nagase M, Hidaka Y, Shirahama Y, Hosomichi K, Nishida Y, Shimoshikiryo I, Hishida A, Katsuura-Kamano S, Shimizu S, Kawaguchi M, Uemura H, Ibusuki R, Hara M, Naito M, Takao M, Nakajima M, Iwasawa S, Nakashima H, Ohnaka K, Nakamura T, Stiburkova B, Merriman TR, Nakatochi M, Ichihara S, Yokota M, Takada T, Saitoh T, Kamatani Y, Takahashi A, Arisawa K, Takezaki T, Tanaka K, Wakai K, Kubo M, Hosoya T, Ichida K, Inoue I, Shinomiya N, Matsuo H. Genome-wide association study revealed novel loci which aggravate asymptomatic hyperuricaemia into gout. Ann Rheum Dis. 2019;78(10):1430–1437. doi: 10.1136/annrheumdis-2019-215521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Matsuo H, Yamamoto K, Nakaoka H, Nakayama A, Sakiyama M, Chiba T, Takahashi A, Nakamura T, Nakashima H, Takada Y, Danjoh I, Shimizu S, Abe J, Kawamura Y, Terashige S, Ogata H, Tatsukawa S, Yin G, Okada R, Morita E, Naito M, Tokumasu A, Onoue H, Iwaya K, Ito T, Takada T, Inoue K, Kato Y, Nakamura Y, Sakurai Y, Suzuki H, Kanai Y, Hosoya T, Hamajima N, Inoue I, Kubo M, Ichida K, Ooyama H, Shimizu T, Shinomiya N. Genome-wide association study of clinically defined gout identifies multiple risk loci and its association with clinical subtypes. Ann Rheum Dis. 2016;75(4):652–659. doi: 10.1136/annrheumdis-2014-206191. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Wen W, Zheng W, Okada Y, Takeuchi F, Tabara Y, Hwang J-Y, Dorajoo R, Li H, Tsai FJ, Yang X, He J, Wu Y, He M, Zhang Y, Liang J, Guo X, Sheu WHH, Delahanty R, Guo X, Kubo M, Yamamoto K, Ohkubo T, Go MJ, Liu JJ, Gan W, Chen CC, Gao Y, Li S, Lee NR, Wu C, Zhou X, Song H, Yao J, Lee IT, Long J, Tsunoda T, Akiyama K, Takashima N, Cho YS, Ong RTH, Lu L, Chen CH, Tan A, Rice TK, Adair LS, Gui L, Allison M, Lee WJ, Cai Q, Isomura M, Umemura S, Kim YJ, Seielstad M, Hixson J, Xiang YB, Isono M, Kim BJ, Sim X, Lu W, Nabika T, Lee J, Lim WY, Gao YT, Takayanagi R, Kang DH, Wong TY, Hsiung CA, Wu IC, Juang JMJ, Shi J, Choi BY, Aung T, Hu F, Kim MK, Lim WY, Wang TD, Shin MH, Lee J, Ji BT, Lee YH, Young TL, Shin DH, Chun BY, Cho MC, Han BG, Hwu CM, Assimes TL, Absher D, Yan X, Kim E, Kuo JZ, Kwon S, Taylor KD, Chen YDI, Rotter JI, Qi L, Zhu D, Wu T, Mohlke KL, Gu D, Mo Z, Wu JY, Lin X, Miki T, Tai ES, Lee JY, Kato N, Shu XO, Tanaka T. Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index. Hum Mol Genet. 2014;23(20):5492–5504. doi: 10.1093/hmg/ddu248. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Liu Y-T, Tantoh DM, Wang L, Nfor ON, Hsu S-Y, Ho C-C, Lung CC, Chang HR, Liaw YP. Interaction between coffee drinking and TRIB1 rs17321515 single nucleotide polymorphism on coronary heart disease in a Taiwanese population. Nutrients. 2020;12(5):1301. doi: 10.3390/nu12051301. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Chang S-L, Nfor ON, Ho C-C, Lee K-J, Lu W-Y, Lung C-C, Tantoh DM, Hsu SY, Chou MC, Liaw YP. Combination of exercise and vegetarian diet: relationship with high density-lipoprotein cholesterol in Taiwanese adults based on MTHFR rs1801133 polymorphism. Nutrients. 2020;12(6):1564. doi: 10.3390/nu12061564. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Su C-L, Tantoh DM, Chou Y-H, Wang L, Ho C-C, Chen P-H, et al. Blood-based SOX2-promoter methylation in relation to exercise and PM2. 5 exposure among Taiwanese adults. Cancers. 2020;12(2):504. doi: 10.3390/cancers12020504. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Shiraishi H, Une H. The effect of the interaction between obesity and drinking on hyperuricemia in Japanese male office workers. J Epidemiol. 2009;19(1):12–16. doi: 10.2188/jea.JE20080016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Yamanaka H, Kamatani N, Hakoda M, Terai C, Kawaguchi R, Kashiwazaki S. Analysis of the genotypes for aldehyde dehydrogenase 2 in Japanese patients with primary gout. Boston: Purine and Pyrimidine Metabolism in Man VIII: Springer; 1995. p 53–6. [DOI] [PubMed]
- 37.Wang Y, Zhang Y, Zhang J, Tang X, Qian Y, Gao P, Zhu D. Association of a functional single-nucleotide polymorphism in the ALDH2 gene with essential hypertension depends on drinking behavior in a Chinese Han population. J Hum Hypertens. 2013;27(3):181–186. doi: 10.1038/jhh.2012.15. [DOI] [PubMed] [Google Scholar]
- 38.Campion EW, Glynn RJ, Delabry LO. Asymptomatic hyperuricemia. Risks and consequences in the Normative Aging Study. Am J Med. 1987;82(3):421–426. doi: 10.1016/0002-9343(87)90441-4. [DOI] [PubMed] [Google Scholar]
- 39.Shadick NA, Kim R, Weiss S, Liang MH, Sparrow D, Hu H. Effect of low level lead exposure on hyperuricemia and gout among middle aged and elderly men: the normative aging study. J Rheumatol. 2000;27(7):1708–1712. [PubMed] [Google Scholar]
- 40.Hochberg MC, Thomas J, Johniene Thomas D, Mead L, Levine DM, Klag MJ. Racial differences in the incidence of gout. Arthritis Rheum. 1995;38(5):628–632. doi: 10.1002/art.1780380508. [DOI] [PubMed] [Google Scholar]
- 41.Faller J, Fox IH. Ethanol-induced hyperuricemia: evidence for increased urate production by activation of adenine nucleotide turnover. N Engl J Med. 1982;307(26):1598–1602. doi: 10.1056/NEJM198212233072602. [DOI] [PubMed] [Google Scholar]
- 42.Gibson T, Rodgers A, Simmonds H, Toseland P. Beer drinking and its effect on uric acid. Rheumatology. 1984;23(3):203–209. doi: 10.1093/rheumatology/23.3.203. [DOI] [PubMed] [Google Scholar]
- 43.Tai V, Narang RK, Gamble G, Cadzow M, Stamp LK, Merriman TR, et al. Do serum urate–associated genetic variants differentially contribute to gout risk according to body mass index? Analysis of the UK Biobank. Arthritis Rheumatol. 2020;72(7):1184–91. [DOI] [PubMed]
- 44.Juraschek SP, Miller ER, III, Gelber AC. Body mass index, obesity, and prevalent gout in the United States in 1988–1994 and 2007–2010. Arthritis Care Res. 2013;65(1):127–132. doi: 10.1002/acr.21791. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Choi HK, Atkinson K, Karlson EW, Curhan G. Obesity, weight change, hypertension, diuretic use, and risk of gout in men: the health professionals follow-up study. Arch Intern Med. 2005;165(7):742–748. doi: 10.1001/archinte.165.7.742. [DOI] [PubMed] [Google Scholar]
- 46.Williams PT. Effects of diet, physical activity and performance, and body weight on incident gout in ostensibly healthy, vigorously active men. Am J Clin Nutr. 2008;87(5):1480–1487. doi: 10.1093/ajcn/87.5.1480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Soriano LC, Rothenbacher D, Choi HK, Rodríguez LAG. Contemporary epidemiology of gout in the UK general population. Arthritis Res Ther. 2011;13(2):R39. doi: 10.1186/ar3272. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Maynard JW, DeMarco MAM, Baer AN, Köttgen A, Folsom AR, Coresh J, et al. Incident gout in women and association with obesity in the Atherosclerosis Risk in Communities (ARIC) Study. Am J Med. 2012;125(7):717. e9–717.e17. doi: 10.1016/j.amjmed.2011.11.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.McAdams-DeMarco MA, Maynard JW, Baer AN, Coresh J. Hypertension and the risk of incident gout in a population-based study: the Atherosclerosis Risk in Communities cohort. J Clin Hypertens. 2012;14(10):675–679. doi: 10.1111/j.1751-7176.2012.00674.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Chen JH, Pan WH, Hsu CC, Yeh WT, Chuang SY, Chen PY, Chen HC, Chang CT, Huang WL. Impact of obesity and hypertriglyceridemia on gout development with or without hyperuricemia: a prospective study. Arthritis Care Res. 2013;65(1):133–140. doi: 10.1002/acr.21824. [DOI] [PubMed] [Google Scholar]
- 51.Lin K-C, Lin H-Y, Chou P. Community based epidemiological study on hyperuricemia and gout in Kin-Hu, Kinmen. J Rheumatol. 2000;27(4):1045–1050. [PubMed] [Google Scholar]
- 52.Aune D, Norat T, Vatten LJ. Body mass index and the risk of gout: a systematic review and dose–response meta-analysis of prospective studies. Eur J Nutr. 2014;53(8):1591–1601. doi: 10.1007/s00394-014-0766-0. [DOI] [PubMed] [Google Scholar]
- 53.Dalbeth N, Pool B, Yip S, Cornish J, Murphy R. Effect of bariatric surgery on the inflammatory response to monosodium urate crystals: a prospective study. Ann Rheum Dis. 2013;72(9):1583–1584. doi: 10.1136/annrheumdis-2013-203545. [DOI] [PubMed] [Google Scholar]
- 54.Yu Y, Yang J, Fu S, Xue Y, Liang M, Xuan D, Zhu X, Wan W, Lv L, Zou H. Leptin promotes monosodium urate crystal–induced inflammation in human and murine models of gout. J Immunol. 2019;202(9):2728–2736. doi: 10.4049/jimmunol.1801097. [DOI] [PubMed] [Google Scholar]
- 55.Wallace KL, Riedel AA, Joseph-Ridge N, Wortmann R. Increasing prevalence of gout and hyperuricemia over 10 years among older adults in a managed care population. J Rheumatol. 2004;31(8):1582–1587. [PubMed] [Google Scholar]
- 56.Facchini F, Chen Y-DI, Hollenbeck CB, Reaven GM. Relationship between resistance to insulin-mediated glucose uptake, urinary uric acid clearance, and plasma uric acid concentration. Jama. 1991;266(21):3008–3011. doi: 10.1001/jama.1991.03470210076036. [DOI] [PubMed] [Google Scholar]
- 57.Quinones Galvan A, Natali A, Baldi S, Frascerra S, Sanna G, Ciociaro D, Ferrannini E. Effect of insulin on uric acid excretion in humans. Am J Physiol Endocrinol Metab. 1995;268(1):E1–E5. doi: 10.1152/ajpendo.1995.268.1.E1. [DOI] [PubMed] [Google Scholar]
- 58.Matsuura F, Yamashita S, Nakamura T, Nishida M, Nozaki S, Funahashi T, Matsuzawa Y. Effect of visceral fat accumulation on uric acid metabolism in male obese subjects: visceral fat obesity is linked more closely to overproduction of uric acid than subcutaneous fat obesity. Metabolism. 1998;47(8):929–933. doi: 10.1016/S0026-0495(98)90346-8. [DOI] [PubMed] [Google Scholar]
- 59.Rathmann W, Funkhouser E, Dyer AR, Roseman JM. Relations of hyperuricemia with the various components of the insulin resistance syndrome in young black and white adults: the CARDIA study. Ann Epidemiol. 1998;8(4):250–261. doi: 10.1016/S1047-2797(97)00204-4. [DOI] [PubMed] [Google Scholar]
- 60.Tanunyutthawongse C, Khuancharee K, Wannaiampikul S. Relationship between serum uric acid and lipid profiles in Thai adults. Ind J Public Health Res Dev. 2020;11(3):2390–397.
- 61.Liang J, Jiang Y, Huang Y, Song W, Li X, Huang Y, et al. The comparison of dyslipidemia and serum uric acid in patients with gout and asymptomatic hyperuricemia: a cross-sectional study. Lipids Health Dis. 2020;19(1):1–7. doi: 10.1186/s12944-020-1197-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from Taiwan Biobank but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are however available from Professor Yung Po Liaw (email address, Liawyp@csmu.edu.tw; tel, + 886424730022 ext. 12102) upon reasonable request and with permission of Taiwan Biobank.