Cigarette Smoking and the Risk of Incident Gout in a Prospective Cohort Study

The relationship between education attainment and gout, and the mediating role of modifiable risk factors: a Mendelian randomization study

Objective

To investigate the causal relationship between educational attainment (EA) and gout, as well as the potential mediating effects of individual physical status (IPS) such as body mass index (BMI) and systolic blood pressure (SBP) and lifestyle habits (LH) including alcohol intake frequency (drinking), current tobacco smoking (smoking), and time spent watching television (TV).

Methods

Utilizing two-sample Mendelian randomization (MR), we analyzed the causal effects of EA on gout risk, and of IPS (BMI and SBP) and LH (smoking, drinking, and TV time) on gout risk. Multivariable MR (MVMR) was employed to explore and quantify the mediating effects of IPS and LH on the causal relationship between EA and gout risk.

Results

An elevation of educational attainment by one standard deviation (4.2 years) exhibited a protective effect against gout (odds ratio 0.724, 95% confidence interval 0.552-0.950; p = 0.020). We did not observe a causal relationship between smoking and gout, but BMI, SBP, drinking, and TV time were found to be causal risk factors for gout. Moreover, BMI, SBP, drinking, and TV time acted as mediating factors in the causal relationship between EA and gout risk, explaining 27.17, 14.83, 51.33, and 1.10% of the causal effects, respectively.

Conclusion

Our study indicates that having a genetically predicted higher level of EA may provide protection against gout. We found that this relationship is influenced by IPS factors such as BMI and SBP, as well as LH including drinking and TV time.

Dyslipidemia and hyperuricemia: a cross-sectional study of residents in Wuhu, China

BACKGROUND

While dyslipidemia has been recognized as a potential risk factor for hyperuricemia, there is currently a dearth of large-scale data specifically focused on studying the relationship between these two conditions. To address this gap, the present study analyzed a dataset of 298,891 physical examination records to investigate in greater detail the clinical classification and compositional relationship between hyperuricemia and dyslipidemia.

METHODS

For this investigation, a cross-sectional research design was utilized to analyze physical examination data that was gathered from Yijishan Hospital in Wuhu, China between 2011 and 2016. Logistic regression was employed to examine the association between hyperuricemia and dyslipidemia. Furthermore, the association between hyperuricemia and dyslipidemia was evaluated based on the clinical classifications of dyslipidemia and its components.

RESULTS

A total of 298,891 participants from China (124,886 [41.8%] females) were included in the study, with an age range of 18 to 90 years (mean [SD]: 47.76 [13.54] years). In multivariate analysis, the odds of hyperuricemia was 1.878 times higher in patients with dyslipidemia compared to those without dyslipidemia (95% confidence interval [CI]: 1.835-1.922). In the clinical classification of dyslipidemia, individuals with hypertriglyceridemia and mixed hyperlipidemia had 1.753 times (95% CI: 1.706-1.802) and 1.925 times (95% CI: 1.870-1.982) higher odds of hyperuricemia, respectively, compared to those without dyslipidemia. Among the components of dyslipidemia, the odds ratios for hyperuricemia in individuals in the fourth quartile compared to those in the first quartile were 3.744 (95% CI: 3.636-3.918) for triglycerides, 1.518 (95% CI: 1.471-1.565) for total cholesterol, and 1.775 (95% CI: 1.718 - 1.833) for non-high-density lipoprotein cholesterol.

CONCLUSIONS

Dyslipidemia has been independently linked with hyperuricemia. Moreover, the elevation of triglycerides or total cholesterol levels, including conditions such as hypertriglyceridemia and mixed hyperlipidemia, have been observed to have a positive association with the development of hyperuricemia.

Single-nucleotide polymorphisms link gout with health-related lifestyle factors in Korean cohorts

Gout-a very painful inflammatory arthritis caused by the deposition of monosodium urate crystals in the joints-is influenced by several factors. We identified the association of single- nucleotide polymorphisms (SNPs) that link gout with health-related lifestyle factors using genomic data from the Korean Genome and Epidemiology Study. We conducted a genome-wide association study (GWAS) on 18,927 samples of 438 Korean patients with gout and 18,489 controls for the discovery stage. For the replication stage, another batch containing samples of 326 patients with gout and 2,737 controls were analyzed. Lastly, a meta-analysis was performed using these two cohorts. We analyzed the effects of health-related lifestyle factors, including eating habits, physical activity, drinking behavior, and smoking behavior, on gout. After identifying the association between GWAS-derived SNPs and health-related lifestyle factors, we confirmed the interaction between the polygenic risk score (PRS) and health-related lifestyle factors. We identified 15 SNPs related to gout, among which rs1481012 of ABCG2 located on chromosome 4 has been newly discovered (P = 2.46e-11). On examining the interaction between SNPs and health-related lifestyles, rs3109823-located in ABCG2-was found to be associated with smoking status. In addition, rs11936395-located in SLC2A9-was significantly associated with the average momentum of exercise per session, whereas rs11066325 located in PTPN11, showed a significant association with the number of exercise sessions per week, smoking status, drinking status, and amount of soju drink per session. rs9421589-located in FAM35A-was significantly associated with the duration of smoking. In addition, we verified that the association between PRS and duration of smoking affects gout. Thus, in this study, we identified novel SNPs that link gout with health-related lifestyle factors in the Korean population.

Risk Factors for Hyperuricemia or Gout in Men and Women: The Circulatory Risk in Communities Study (CIRCS)

AIM

We aimed to examine sex-specific risk factors for hyperuricemia or gout in Japanese cohorts.

METHODS

We followed up 3,188 men (mean age, 55.6 years) and 6,346 women (mean age, 54.1 years) without hyperuricemia, gout, or elevated liver enzymes at baseline from 1986 to 1990 for a median of 14.6 years. The participants were considered as having hyperuricemia or gout if their serum uric acid levels were ≥ 7.0 mg/dL or they were receiving treatment for hyperuricemia or gout during annual health checkups. The sex-specific multivariable hazard ratios (HRs) of hyperuricemia or gout incidence were calculated after adjustment for smoking and drinking status, body mass index, hypertension, diabetes, hypercholesterolemia, and hypertriglyceridemia using the Cox proportional-hazard model.

RESULTS

During follow-up, 733 men and 355 women had hyperuricemia or gout. Among men, the multivariable HRs (95% confidence intervals) of hyperuricemia or gout were 1.23 (1.00-1.52) and 1.41 (1.13-1.75) for drinkers of ＜46 and ≥ 46 g ethanol/day, respectively, compared with non-drinkers; 1.00 (0.81-1.24) and 1.18 (0.93-1.50) for smokers of 1-19 and ≥ 20 cigarettes/day, respectively, compared with never smokers; and 1.41 (1.20-1.65) for hypertensive compared with non-hypertensive participants. The HRs for women were 1.02 (0.70-1.48), 1.66 (1.05-2.63), and 1.12 (0.88-1.42) for current drinkers, current smokers, and hypertensive participants, respectively. For both men and women, body mass index, diabetes, hypercholesterolemia, and hypertriglyceridemia were not associated with hyperuricemia or gout incidence.

CONCLUSIONS

Hypertension and alcohol drinking are risk factors for hyperuricemia or gout among men and smoking among women.

Investigating the Effect of Cigarette Smoking on Serum Uric Acid Levels in Multiple Sclerosis Patients: A Cross Sectional Study

OBJECTIVES

The present study is aimed at determining the effect of cigarette smoking (CS) on serum uric acid (UA) levels quantitatively before and after smoking cessation among people with MS (pwMS). Additionally, a possible correlation between UA levels and both disability progression and disease severity was also investigated. A retrospective cross-sectional study was conducted using the Nottingham University Hospitals MS Clinics database. It involves 127 people with definite MS recorded when reporting the latest smoking status and the clinical diagnosis. All necessary demographics and clinical characteristics were collected. We found that smoker pwMS had significantly lower serum UA levels than non-smoker pwMS (p-value = 0.0475), and this reduction was recovered after smoking cessation (p-value = 0.0216). However, the levels of disability or disease severity were not correlated with the levels of serum UA in current smoker pwMS, measured by the expanded disability status scale (EDSS; r = -0.24; p-value = 0.38), multiple sclerosis impact scale 29 (MSIS-29; r = 0.01; p-value = 0.97) and MS severity score (MSSS; r = -0.16; p-value = 0.58), respectively. Our result suggests that the reduction in UA levels is more likely a consequence of oxidative stress triggered by many risk factors, including CS, and could be considered a potential indicator of smoking cessation. In addition, the absence of a correlation between UA levels and disease severity and disability suggests that UA is not an optimal biomarker for disease severity and disability prediction among current smoker, ex-smoker or non-smoker pwMS.

Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis

Background

The burden of gout is increasing worldwide, which places a heavy burden on society and healthcare systems. This study investigates the independent effects of age, period, and cohort on the gout prevalence from 1990 to 2019 in China, compares these effects by gender and then predicts the future burden of gout over the next decade.

Methods

The data were obtained from the Global Burden of Disease (GBD) study in 2019. Joinpoint regression model was employed to calculate the annual percentage change (APC) in gout prevalence, and the age-period-cohort analysis was utilized to estimate the independent effects of age, period, and cohort. ARIMA model was extended to predict the gout epidemic in 2020-2029.

Results

In 2019, there were 16.2 million cases of gout in China, with an age-standardized prevalence rate (ASPR) of 12.3‰ and 3.9‰ in men and women, respectively. During 1990-2019, the ASPR of gout was increasing significantly, with an average APC of 0.9%. The periods of 2014-2017 and 2001-2005 were "joinpoint" for men and women (APC: 6.3 and 5.6%). The age-period-cohort analyses revealed that the relative risk (RR) of developing gout increased with age, peaking at 70-74 years in men (RR_age(70-74) = 162.9) and 75-79 years in women (RR_age(75-79)=142.3). The period effect trended upward, with a more rapid increase in women (RR_period(2019) = 2.31) than men (RR_period(2019) = 2.23). The cohort effect generally peaked in the earlier cohort born in 1905-1909 for both sexes. Gout prevalence showed a strong positive correlation with the consumption of meat and aquatic products (r_meat = 0.966, r_{aquaticproducts} = 0.953). Within 2029, the ASPR of gout was projected to be 11.7‰ and 4.0‰ in men and women, respectively.

Conclusion

The prevalence of gout is increasing at an alarming rate in China; thus, it is necessary to provide targeted health education, regular screening, and accessible urate-lowering therapy healthcare to prevent and protect against gout in China, particularly in older women.

Environmental factors and risk of gout

Gout is a chronic disease with inflammatory arthritis caused by monosodium urate (MSU) crystals deposition, an elevated serum urate level (hyperuricaemia) is the critical factor leading to MSU crystals deposition and promoting the progression of gout. The onset and development of gout is generally the result of multiple factors, such as diet, heredity and environmental factors. Although genetics and diet are thought to play as major factors, a growing body of research evidence has highlighted that environmental factors also play a significant role in the onset and exacerbation of gout. Recent studies have shown that air pollutants such as particulate matter, sulfur dioxide (SO₂) and carbon monoxide (CO) may increase the risk of hospitalizations for gout, and that the changes in temperature and humidity may affect uric acid (UA) levels. There is also seasonal trend in gout. It has been demonstrated that environmental factors may induce or accelerate the production and release of pro-inflammatory mediators, causing an unbalance oxidative stress and systemic inflammation, and then participating in the overall process or a certain link of gout. Moreover, several environmental factors have shown the ability to induce the production urate and regulate the innate immune pathways, involving in the pathogenesis of gout. Nevertheless, the role of environmental factors in the etiology of gout remains unclear. In this review, we summarized the recent literatures and aimed to discuss the relationship between environmental factors (such as microclimate, season, ambient/indoor air pollution and extreme weather) and gout. We further discussed the inflammatory mechanisms of environmental factors and gout and the comprehensive effects of environmental factors on gout. We also made a prospect of the management and treatment of gout, with special consideration to environmental factors associated with gout.

Healthy lifestyle counteracts the risk effect of genetic factors on incident gout: a large population-based longitudinal study

BACKGROUND

Risk genes linked to the development of gout have been identified, and lifestyle factors are related to gout risk. It remains unclear whether healthy lifestyle factors can mitigate the genetic risk of gout. Therefore, we aimed to explore whether and to what extent a healthy lifestyle can mitigate the risk of gout related to genetic factors.

METHODS

Within the UK Biobank, 416,481 gout-free participants (aged 37-74) were identified at baseline. Polygenic risk for gout was assessed and categorized as low (lowest tertile), middle (tertile 2), and high (highest tertile). Healthy lifestyle factors included no/moderate alcohol consumption, no smoking, physical activity, and a healthy diet. Participants were categorized into three groups according to their number of healthy lifestyle factors: unfavorable (0 or 1), intermediate (any 2), and favorable (3 or 4). Data were analyzed using Cox proportional hazard models.

RESULTS

Over the follow-up (median: 12.1 years), 6206 participants developed gout. Compared to low genetic risk, the hazard ratios (HRs) and 95% confidence intervals (CIs) of gout was 1.44 (1.35-1.54) for middle and 1.77 (1.66-1.89) for high genetic risk. The HRs (95% CIs) of gout were 0.63 (0.59-0.67) for a favorable lifestyle and 0.79 (0.75-0.85) for an intermediate lifestyle, compared to an unfavorable lifestyle. In joint effect analysis, compared to participants with low genetic predisposition and a favorable lifestyle, the HRs (95% CIs) of gout were 2.39 (2.12-2.70)/3.12 (2.79-3.52) in those with middle and high genetic predisposition plus unfavorable lifestyle profiles, and 1.53 (1.35-1.74)/1.98 (1.75-2.24) for those with middle and high genetic predisposition plus favorable lifestyle profiles, respectively. Moreover, compared to an unfavorable lifestyle, the HRs of gout related to a favorable lifestyle was 0.64 (95% CI, 0.56-0.73) for low genetic risk, 0.65 (95% CI, 0.58-0.72) for middle genetic risk, and 0.62 (95% CI, 0.57-0.69) for high genetic risk. There was a significant additive interaction between unfavorable lifestyle and high genetic risk on gout.

CONCLUSIONS

Healthy lifestyle was associated with a lower risk of gout and may attenuate the risk of gout related to genetic factors by almost a third.

Association of self-reported snoring and hyperuricaemia: a large cross-sectional study in Chongqing, China

OBJECTIVE

To examine the relationship between self-reported snoring and hyperuricaemia in a large-scale population in Chongqing, China.

SETTING

Face-to-face electronic questionnaire survey, physical examination and biological sample testing were conducted in 13 districts of Chongqing. Chongqing is a municipality in southwest China.

PARTICIPANTS

In this study, 23 308 Han ethnicity permanent residents aged 30-79 years were recruited. Individuals missing data were excluded, 22 389 subjects were included in final analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

Serum uric acid (UA) was measured using an oxidase method. Hyperuricaemia was defined as serum UA >420 µmol/L in men and >360 µmol/L in women. Information about self-reported snoring was obtained by questionnaire survey. All participants were divided into 'no snoring' 'snoring occasionally' and 'snoring frequently'. Multivariable logistic regression analysis was performed to assess the relationship between self-reported snoring and hyperuricaemia.

RESULTS

The prevalence of hyperuricaemia was 14.43%, and snorers were more likely to have hyperuricaemia than non-snorer in different age and gender groups. For the total population, those who snore occasionally or frequently were more likely to be hyperuricaemia (OR 1.19, 95% CI 1.07 to 1.31; OR 1.33, 95% CI 1.19 to 1.47) compared with no snoring people. Stratification by age, gender and body mass index (BMI), we found that the positive association between snoring frequently and hyperuricaemia was insisted in different age, gender and high BMI groups, and the strength of association varied with different age, gender and BMI category.

CONCLUSION

Snoring frequency was positively associated with higher risk of hyperuricaemia. Snoring frequently may be a signal for hyperuricaemia, especially for women, those over 59 years of age, or those who are overweight or obese.

Monocyte to high-density lipoprotein cholesterol ratio and serum uric acid in Chinese adults: a cross-sectional study

BACKGROUND

Previous studies have shown that the monocyte to high-density lipoprotein cholesterol (HDL-C) ratio (MHR) is a predictor of various diseases such as coronary heart disease, diabetic microangiopathy, and metabolic syndrome. However, there are few scientific reports on the correlation between MHR and serum uric acid. The objective of this report is to explore the relationship between MHR and serum uric acid in Chinese adults.

METHODS

This cross-sectional study included 646 participants from southwest China who underwent a health examination at the Health Management Center of Deyang People's Hospital. The examination included blood pressure readings, routine blood tests (lipid, fasting glucose, serum transaminase, and serum uric acid levels), and various standardized questionnaires. We employed a generalized additive model and smoothed curve fitting to explore the relationship between MHR and serum uric acid levels. We then performed subgroup analyses to investigate the robustness of this relationship.

RESULTS

After adjusting for confounders (age, sex, body mass index, systolic blood pressure, diastolic blood pressure, aspartate transaminase, alanine aminotransferase, fasting glucose, total cholesterol, low-density lipoprotein, smoking, drinking, and exercise status), MHR was found to be positively correlated with serum uric acid levels (P < 0.001). The smoothing curve showed an approximately linear correlation between MHR and serum uric acid levels, and the linear correlation coefficient was 146.74 (95% CI 96.16-197.33, P < 0.0001). The subgroup analyses showed that the effect of MHR on serum uric acid levels was smaller in occasional smokers and smokers than in nonsmokers (P = 0.0194).

CONCLUSION

MHR was significantly and positively correlated with serum uric acid levels. Additionally, the effect of MHR on serum uric acid levels was lower in the individuals who smoked more.

Factors Influencing the Serum Uric Acid in Gout with Cerebral Infarction

Background

Although the relationship between gout and cardiovascular has been well demonstrated, there is little information about the difference between gout with cerebrovascular disease and cardiovascular disease. In this study, the differences between gout with cerebral infarction (gout+CI) and gout with coronary heart disease (gout+CHD) and related factors that affect serum uric acid (sUA) levels in gout+CI were investigated by a cross-sectional study.

Method

The patients from Jiangxi Provincial People's Hospital with gout+CHD, gout+CI, and gout with coronary heart disease and cerebral infarction (gout+CHD+CI) between 2016 and 2020 were included in this study, and the medical record data were collected and analyzed.

Results

We observed significant differences in age, drinking, hypertension, long-term use of diuretics and NSAIDs, sUA, CRE, and blood glucose in patients with gout+CHD and gout+CI. The sUA level was significantly positively correlated with smoking, CRE, and TG in the gout+CI group and was only positively correlated with CRE in the gout+CHD group and the gout+CHD+CI group (p < 0.05). Interestingly, the sUA level was only negatively correlated with the age and gender in the gout+CI group (p < 0.05). After excluding factors with no significant statistical effect, only age, gender, smoking, CRE, and TG were included in the multiple linear regression model. It suggested that smoking, CRE, and TG are positively correlated with the sUA level, while age was negatively correlated with the sUA level.

Conclusions

There are many discrepancies in clinical characteristics between gout+CHD patients and gout+CI patients, especially that the factors that affect UA levels are significantly different. The data also suggested that uric acid-lowering therapy may need to be strengthened in the young gout+CI patients with a history of smoking.

Second-Hand Smoke and Its Synergistic Effect with a Body-Mass Index of >24.9 kg/m2 Increase the Risk of Gout Arthritis in Indonesia

To analyze the association between smoking status (active smoking and exposure to Second-Hand Smoking (SHS)) and the synergistic effect of smoking status and BMI with gout risk, a community-based case-control design was undertaken among 385 participants, including 304 healthy controls and 81 gout patients from seven community health services. Adjusted Odd Ratios (AORs) and 95% Confidence Interval (CIs) of gout for active smoking and SHS were 3.26 (95% CI = 1.07~9.90) and 4.67 (95% CI = 2.18~10.00) compared to non-smokers. Time-dependent manner of active smoking and SHS significantly increased gout risk with AORs and 95% CIs of 5.95 (1.41~25.03) and 10.12 (3.51~29.14). Dose-dependency of active smokers and SHS showed AORs and 95% CIs of 5.15 (1.28~20.63) and 4.37 (1.33~14.28). Smoking 20 cigarettes (one pack) per day for one year is equivalent to one pack-year. Active smoking >20 pack-year and SHS > 26.5 pack-year increased gout risk with AORs and 95% CIs of 7.18 (1.53~33.67) and 9.95 (3.64~27.22). Participants who smoked (active smoking and SHS) and with Body Mass Index (BMI) of > 24.9 kg/m2 synergistically increased gout risk, with an AOR of 9.65 and 95% CI of 3.25~28.65, compared to BMI ≤ 24.9 kg/m2 and non-smoker. Smoking status (active smoking and SHS) and the synergistic effect of smoking status and BMI increased gout risk in Indonesia.

Behavioral Characteristics of Gout Patients and Their Impact on the Results of Urate Lowering Therapy

Background. Gout is frequently accompanied by hypertension, obesity, and/or impaired glucose tolerance, which are often complicated with heavy smoking and dietary violations, especially in male patients.

Objective. To determine the behavioral characteristics of gout patients that could impact the results of urate lowering therapy.

Subjects and methods. The relationship between behavioral characteristics and results of urate lowering therapy were investigated in 74 male gout patients of Chengdu Rheumatism Hospital. The results of treatment were evaluated using serum uric acid contents before and after treatment, VAS pain score before and after treatment. Behavioral characteristics for the last ten years (smoking status, daily volume of drinking water, etc.) were accessed by means of retrospective survey.

Results. In gout patients with poor treatment response, serum uric acid at the beginning of the treatment was already significantly lower (365.76 ± 163.06 μmol/L); this trend was also noted in a “slow progress” group, while patients with higher serum uric acid before treatment had notably better response to urate lowering therapy. During further analysis age negatively correlated with serum uric acid (r = –0.328; p = 0.002) and uric acid clearance ratio (r = –0.299; p = 0.002).

In patients with uric acid clearance ratio above 40 % the prevalence of kidney diseases (stones or dysfunction) was significantly lower compared to other groups. There was no significant influence of hypertension, diabetes mellitus, fatty liver or hyperlipidaemia on uric acid clearance ratio (p > 0.05).

Amount of drinking water also influenced the serum uric acid clearance ratio. Bigger amount of patients in the “fast progress” group (40.0 % compared to 30.44 and 25.0 %) tended to drink more water.

Conclusion. In most gout patients, serum uric acid levels before treatment acted as the reliable predictor of good response to urate lowering therapy. Treatment response (serum uric acid clearance ratio) correlated positively with the hyperuricemia and drinking sufficient amounts of water, negatively – with prolonged smoking (more than 10 years) and age.

The absolute risk of gout by clusters of gout-associated comorbidities and lifestyle factors-30 years follow-up of the Malmö Preventive Project

Background

Gout is predicted by a number of comorbidities and lifestyle factors. We aimed to identify discrete phenotype clusters of these factors in a Swedish population-based health survey. In these clusters, we calculated and compared the incidence and relative risk of gout.

Methods

Cluster analyses were performed to group variables with close proximity and to obtain homogenous clusters of individuals (n = 22,057) in the Malmö Preventive Project (MPP) cohort. Variables clustered included obesity, kidney dysfunction, diabetes mellitus (DM), hypertension, cardiovascular disease (CVD), dyslipidemia, pulmonary dysfunction (PD), smoking, and the use of diuretics. Incidence rates and hazard ratios (HRs) for gout, adjusted for age and sex, were computed for each cluster.

Results

Five clusters (C1–C5) were identified. Cluster C1 (n = 16,063) was characterized by few comorbidities. All participants in C2 (n = 750) had kidney dysfunction (100%), and none had CVD. In C3 (n = 528), 100% had CVD and most participants were smokers (74%). C4 (n = 3673) had the greatest fractions of obesity (34%) and dyslipidemia (74%). In C5 (n = 1043), proportions with DM (51%), hypertension (54%), and diuretics (52%) were highest. C1 was by far the most common in the population (73%), followed by C4 (17%). These two pathways included 86% of incident gout cases. The four smaller clusters (C2–C5) had higher incidence rates and a 2- to 3-fold increased risk for incident gout.

Conclusions

Five distinct clusters based on gout-related comorbidities and lifestyle factors were identified. Most incident gout cases occurred in the cluster of few comorbidities, and the four comorbidity pathways had overall a modest influence on the incidence of gout.

Prevalence and associated factors of hyperuricemia among urban adults aged 35-79 years in southwestern China: a community-based cross-sectional study

Hyperuricemia is prevalent throughout the world. However, a well-designed large-scale epidemiological investigation of hyperuricemia in southwestern China is lacking. A regional representative sample of 10,141 participants were included using multistage, stratified sampling in Chengdu and Chongqing from September 2013 to March 2014. Hyperuricemia was defined as the self-reported of the doctor's diagnosis of hyperuricemia, or serum uric acid > 420 μmol/L in men or serum uric acid > 360 μmol/L in women. The overall age- and sex-standardized prevalence of hyperuricemia among adults aged 35-79 years was 13.5%. Compared with women, the prevalence of hyperuricemia in men was higher (17.3% versus 10.0%). Hypertension, hyperlipidemia, overweight or obesity, central obesity were associated with an increased risk for hyperuricemia both in men and in women. Married men and women were not susceptible to hyperuricemia. Current cigarette smoking was an associated risk factor of hyperuricemia only in women. Hyperuricemia has become a major health problem among urban adults aged 35-79 years in southwestern China, and special attention should be paid to men. Comorbidities associated with hyperuricemia and causality worth further investigation.

Association of sleep quality and sleep duration with serum uric acid levels in adults

OBJECTIVE

To date, the association between sleep duration or sleep quality and hyperuricemia has remained unclear. In addition, sleep duration and quality were not considered concomitantly in previous studies. Thus, this study was aimed toward an examination of the association of sleep duration and quality with uric acid level in a Taiwanese population.

METHODS

A total of 4,555 patients aged ≥18 years were enrolled in this study. The sleep duration was classified into three groups: short (<7 h), normal (7-9 h), and long (≥9 h). The Pittsburgh Sleep Quality Index (PSQI) was used to evaluate sleep quality, and poor sleep quality was defined as a global PSQI score of >5.

RESULTS

Poor sleepers were younger and had lower body mass index, blood pressure, uric acid, blood sugar, cholesterol, creatinine level, shorter sleep duration, and engaged in less exercise but had a higher white blood cell count and prevalence of smoking as compared to good sleepers. There were also differences in body mass index, blood pressure, uric acid, blood sugar, lipid profiles, and sleep quality among subjects with different sleep durations. After adjusting for other variables, poor sleep quality was associated with lower uric acid levels. In addition, short sleep duration was positively associated with higher uric acid levels.

CONCLUSIONS

Poor sleep quality was related to lower uric acid levels, whereas short sleep duration was associated with higher uric acid levels.

The haplotype of SLC2A9_rs3733591, PKD2_rs2725220 and ABCG2_rs2231142 increases the hyperuricaemia risk and alcohol, chicken and processed meat intakes and smoking interact with its risk

We determined that a genetic haplotype increased the risk of hyperuricaemia and it interacted with lifestyle factors, including nutrients in 28,445 middle-aged Koreans. ABCG2_rs2231142, PKD2_rs2725220 and SLC2A9_rs3733591 were selected from GWAS based on hyperuricaemia (≥7 mg/dL; p = 6.88E-42, 1.56E-26 and 1.01E-20, respectively). Hyperuricaemia and gout were elevated by 3.93- and 3.23-fold, respectively, by the minor alleles as compared with the major alleles of the haplotype of the selected 3 SNPs after adjusting for covariates. The haplotype significantly interacted with alcohol, chicken and processed meat intakes, and smoking status in the hyperuricaemia risk (p = 0.002-0.007). Minor alleles of the haplotype had an association with hyperuricaemia as compared with major alleles particularly in high intakes of alcohol (2g/day), chicken (6.3g/day), and processed meat (3g/day) and smokers. In conclusion, people carrying minor alleles of the haplotype of SLC2A9_rs3733591, PKD2_rs2725220 and ABCG2_rs2231142 should avoid diets high in chicken and processed meat, alcohol drinking, and cigarette smoking to protect against hyperuricaemia risk.

Uric acid and uric acid to creatinine ratio in the assessment of chronic obstructive pulmonary disease: Potential biomarkers in multicomponent models comprising IL-1beta

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease, with oxidative stress and inflammation implicated in its development. Uric acid (UA) could exert anti-oxidative, pro-oxidative or pro-inflammatory effects, depending on the specific context. It was recently shown that soluble UA, and not just its crystals, could activate the nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome, leading to interleukin (IL)-1β secretion. We aimed to assess the differences in blood levels of UA and its ratio with creatinine (UCR) between COPD patients and healthy subjects, as well as their association with disease severity, smoking status, common COPD comorbidities and therapy regimes. The diagnostic characteristics of UA and UCR were also explored. This study included 109 stable COPD patients and 95 controls and measured white blood cells (WBC), C-reactive protein (CRP), fibrinogen (Fbg), IL-1β, creatinine (CREAT) and UA. All of the parameters were increased in COPD patients, except for CREAT. UA and UCR were positively associated with WBC, CRP and IL-1β. COPD smokers had lower UA and UCR values. Common COPD therapy did not affect UA or UCR, while patients with cardiovascular diseases (CVD) had higher UA, but not UCR, levels. Patients with higher UCR values showed worse disease-related outcomes (lung function, symptoms, quality of life, history of exacerbations, BODCAT and BODEx). Also, UCR differentiated patients with different severity of airflow limitation as well as symptoms and exacerbations. The great individual predictive potential of UCR and IL-1β was observed with their odds ratios (OR) being 2.09 and 5.53, respectively. Multiparameter models of UA and UCR that included IL-1β were able to correctly classify 86% and 90% of cases, respectively. We suggest that UA might be a useful biomarker when combined with IL-1β, while UCR might be even more informative and useful in overall COPD assessments.

Assessment Causality in Associations Between Serum Uric Acid and Risk of Schizophrenia: A Two-Sample Bidirectional Mendelian Randomization Study

Purpose

Although increasing lines of evidence showed associations between serum uric acid (UA) levels and schizophrenia, the causality and the direction of the associations remain uncertain. Thus, we aimed to assess whether the relationships between serum UA levels and schizophrenia are causal and to determine the direction of the association.

Patients and Methods

Two-sample bidirectional Mendelian randomization (MR) analyses and various sensitivity analyses were performed utilizing the summary data from genome-wide association studies within the Global Urate Genetics Consortium and the Psychiatric Genomics Consortium. Secondary MR analyses in both directions were conducted within summary data using genetic risk scores (GRSs) as instrumental variables.

Results

Three MR methods provided no causal relationship between serum UA and schizophrenia. Furthermore, GRS approach showed similar results in the three MR methods after adjustment for heterogeneity. By contrast, inverse variance weighted method, weighted median and GRS approach suggested a causal effect of schizophrenia risk on serum UA after adjustment for heterogeneity (per 10-symmetric percentage increase in schizophrenia risk, beta: -0.039, standard error (SE): 0.013, P = 0.003; beta: -0.036, SE: 0.018, P = 0.043; beta: -0.039, SE: 0.013, P = 0.002; respectively). Moreover, in both directions' analyses, the heterogeneity and sensitivity tests suggested no strong evidence of bias due to pleiotropy.

Conclusion

Schizophrenia may causally affect serum UA levels, whereas the causal role of serum UA concentrations in schizophrenia was not supported by our MR analyses. These findings suggest that UA may be a useful potential biomarker for monitoring treatment or diagnosis of schizophrenia rather than a therapeutic target for schizophrenia.

[Hyperuricemia, gout and high cardiovascular risk - how to manage them in clinical practice]

In recent years, the relationship of hyperuricemia and gout with a high risk of cardiovascular disease has been widely discussed. Therefore, it is important to systematically examine patients in order to diagnose comorbidities, among which cardiovascular disease and its complications occupy a leading place and consider mandatory treatment of patients with hyperuricemia and gout with high cardiovascular risk with lowering drugs, which fully reflects the provisions of the latest European recommendations for the management and treatment of patients with gout.

Association of gout and colorectal cancer in Taiwan: a nationwide population-based cohort study

OBJECTIVES

This study aimed to determine colorectal cancer (CRC) risks among patients with gout through a follow-up study on a nationwide population-based cohort that included patients with gout and the general population in Taiwan.

PARTICIPANT

From the Taiwan National Health Insurance Research Database, we identified 28 061 patients who were newly diagnosed with gout between 2000 and 2010 as the study cohort. We randomly selected 84 248 subjects matching in gender, age and baseline year as comparison cohort. The cohorts were followed up until CRC occurrence, withdrawal from the system of National Health Insurance, or Dec. 31, 2013.

PRIMARY AND SECONDARY OUTCOME MEASURES

Cumulative incidences and incidence rate ratios (IRRs) of CRC between two cohorts were examined. The Cox proportional hazards model was used to evaluate risk factors associated with CRC development.

RESULTS

During the 13-year follow-up, the incidence rate of CRC development in the gout cohort reached 2.44 per 1000 person-years, which was higher than the 2.13 per 1000 person-years in the control cohort (IRR=1.15; 95% CI 1.04 to 1.26). After adjusting for age, gender, urbanisation status and comorbidities, including hypertension, diabetes and hyperlipidaemia, gout showed no significant association with increased risk of CRC occurrence (adjusted HR=1.03; 95% CI 0.93 to 1.14).

CONCLUSIONS

Similar risks of CRC incidence were observed in patients with and without gout in Taiwan. Allopurinol and colchicine are commonly used as urate-lowering drug and anti-inflammation medication in Taiwan and had been shown to reduce the risk of CRC incidence. Thus, further pharmaco-epidemiological studies should be carried out to specifically assess the role of allopurinol in the relationship between gout and CRC.

PET/CT for Diagnosis and Management of Large-Vessel Vasculitis

PURPOSE OF REVIEW

This review aims to discuss the use of fluorodeoxyglucose (FDG) positron emission tomography (PET/CT) for diagnosis and management of patients with large-vessel vasculitis (LVV).

RECENT FINDINGS

Incidence of LVV is likely underestimated, in part due to its non-specific symptoms. Nevertheless, early diagnosis of LVV is essential to initiate timely therapy in order to prevent vascular complications, such as stenoses and aneurysms. FDG PET/CT imaging has the ability to detect LVV during the acute phase, prior to edema and other vascular structural changes, with its high sensitivity for inflammatory activity. FDG PET/CT was shown to be a powerful prognostic marker by allowing identification of patients at risk of vascular complications. Additionally, preliminary data support the use of FDG PET/CT to follow therapy efficacy. FDG PET/CT allows early detection of inflammation, before morphological and irreversible vascular changes can be observed, allowing prompt diagnosis and treatment of LVV.

Association between smoking and serum uric acid in Korean population: Data from the seventh Korea national health and nutrition examination survey 2016

The aim of this study was to identify any association between serum uric acid and smoking status using data from the Seventh Korea National Health and Nutrition Examination Survey (KNHANES VII-1) 2016 of the Korean population.This study used a cross-sectional design and analyzed 5609 subjects aged ≥ 19 years among 8150 participants enrolled in the KNHANES VII-1 2016. Smoking status was classified into current smokers, never smokers, and ex-smokers. Hyperuricemia was defined as > 7.0 mg/dL for men and > 6.0 mg/dL of serum uric acid for women. Association between smoking and serum uric acid/hyperuricemia was assessed by Pearson's or Spearman's correlation analyses and multivariate logistic regression analysis showing odds ratio (OR) and 95% confidence interval (CI).A significant difference in serum uric acid according to smoking status was identified in female (P < .001) but not in male subjects (P = .069). In female subjects, current smokers and ex-smokers showed higher serum uric acid than never smokers (P < 0.001 of both). Serum uric acid was associated with smoking status in female but not male subjects (r = 0.057, P = .001 and r = 0.025, P = .220, respectively). There was significant difference of smoking status between female subjects with and without hyperuricemia (P < .001). Current smokers had 2.7 times higher likely to have hyperuricemia in female, compared to never smokers (OR 2.674, 95% CI 1.578 - 4.531, P < .001).This study revealed that smoking was closely associated with serum uric acid in female but not in male subjects in Korean population.

Assessing the causal association between smoking behavior and risk of gout using a Mendelian randomization study

This study aimed to examine whether smoking behavior is causally related to gout. Summary statistics of publicly available data from genome-wide association studies (GWAS) of smoking behavior (n = 85,997) served as the exposure dataset, while meta-analysis results of 14 studies including 2115 cases and 67,259 controls of European descent served as the outcome dataset. The data were subjected to two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. Five single-nucleotide polymorphisms (SNPs) from GWAS of smoking behavior were selected as instrumental variables (IVs) to improve inference: CHRNA3 (rs1051730), PDE1C (rs215614), CYP2A6 (rs4105144), CHRNB3 (rs6474412), and CYP2B6 (rs7260329). The IVW data did not support a causal association between smoking behavior and gout (beta = - 0.035, SE = 0.036, p = 0.333). MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.021; p = 0.560). MR-Egger analysis revealed no causal association between smoking behavior and gout (beta = - 0.074, SE = 0.070, p = 0.366). The weighted median approach did not support a causal association between smoking behavior and gout (beta = - 0.043, SE = 0.040, p = 0.279). Cochran's Q test indicated no evidence of heterogeneity between IV estimates based on individual variants. The results of "leave one out" analysis demonstrated that no single SNP drove the IVW point estimate. MR estimates using IVW, weighted median, and MR-Egger analysis were consistent and did not support a causal inverse association between smoking behavior and gout.

Association between smoking and gout: a meta-analysis

Previous studies showed that smoking is linked with the decreased risk of gout, but the results remain controversial. The aim of this meta-analysis was to determine the associations between smoking and the risk of gout. A systematic literature search of PubMed and EMBASE was conducted. Data were extracted by two independent reviewers. The pooled odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of associations, using random effects and fixed effects models. Five studies with a total of 17,915,507 participants with 16,880 gouts were enrolled. Heterogeneity among the effect sizes of five studies was reported as I² = 87.9%. Our meta-analysis indicated that smoking (ever- vs non-, OR = 0.87, 95% CI = 0.67-1.12) was not associated with the risk of gout in random effects model, whereas there was an association between smoking (ever- vs non-, OR = 0.70, 95% CI = 0.65-0.74) and gout risk in fixed effects model. Our finding indicates that smoking may not be involved in the risk of gout. However, further studies are still needed to confirm our results.

An association of smoking with serum urate and gout: A health paradox

BACKGROUND

The potential effect of cigarette smoking on levels of serum urate and risk of gout has been considered by a large number of studies, either as the primary variable of interest or as a covariate.

METHODS

Here we systematically review the published evidence relating to the relationship of smoking with serum urate, hyperuricaemia, and gout.

RESULTS

Many studies have reported that smoking reduces serum urate, however, the evidence has not been conclusive with other studies pointing to the opposite or no effect. It has also been suggested that smoking reduces the risk of gout, although there is some evidence to contradict this finding.

CONCLUSION

A consensus has yet to be reached as to the effect of smoking on serum urate levels and the risk of gout.

DNA hypomethylation of a transcription factor binding site within the promoter of a gout risk gene NRBP1 upregulates its expression by inhibition of TFAP2A binding

BACKGROUND

Genome-wide association studies (GWASs) have identified dozens of loci associated with gout, but for most cases, the risk genes and the underlying molecular mechanisms contributing to these associations are unknown. This study sought to understand the molecular mechanism of a common genetic variant, rs780093, in the development of gout, both in vitro and in vivo.

RESULTS

Nuclear receptor binding protein 1 (NRBP1), as a gout risk gene, and its regulatory region, 72 bp upstream of the transcription start site, designated as B1, were identified through integrative analyses of genome-wide genotype and DNA methylation data. We observed elevated NRBP1 expression in human peripheral blood mononuclear cells (PBMCs) from gout patients. In vitro luciferase reporter and protein pulldown assay results showed that DNA methylation could increase the binding of the transcription factor TFAP2A to B1, leading to suppressed gene expression. There results were further confirmed by in vivo bisulfite pyrosequencing showing that hypomethylation on B1 is associated with increased NRBP1 expression in gout patients.

CONCLUSIONS

Hypomethylation at the promoter region of NRBP1 reduces the binding of TFAP2A and thus leads to elevated NRBP1 expression, which might contribute to the development of gout.

Impact of comorbidities on gout and hyperuricaemia: an update on prevalence and treatment options

Gout, the most prevalent inflammatory arthritis worldwide, is associated with cardiovascular and renal diseases, and is an independent predictor of premature death. The frequencies of obesity, chronic kidney disease (CKD), hypertension, type 2 diabetes, dyslipidaemias, cardiac diseases (including coronary heart disease, heart failure and atrial fibrillation), stroke and peripheral arterial disease have been repeatedly shown to be increased in gout. Therefore, the screening and care of these comorbidities as well as of cardiovascular risk factors are of outmost importance in patients with gout. Comorbidities, especially CKD, and drugs prescribed for their treatment, also impact gout management. Numerous epidemiological studies have shown the association of asymptomatic hyperuricaemia with the above-mentioned diseases and cardiovascular risk factors. Animal studies have also produced a mechanistic approach to the vascular toxicity of soluble urate. However, causality remains uncertain because confounders, reverse causality or common etiological factors might explain the epidemiological results. Additionally, these uncertainties remain unsolved despite recent studies using Mendelian randomisation or therapeutic approaches. Thus, large randomised placebo-controlled trials are still needed to assess the benefits of treating asymptomatic hyperuricaemia.

Risk of acute gout among active smokers: data from nationwide inpatient sample

Smoking has been found to be negatively correlated with serum uric acid levels by virtue of reduced production and increased consumption of endogenous antioxidant uric acid among smokers and has been reported to decrease incidence of gout. To shed further light on the question of association between active smoking and acute gout by examining this association using a large inpatient US database, using the Nationwide Inpatient Sample data from 2009 to 2011, we identified current smokers based on the International Classification of Diseases, Ninth Revision (ICD-9) code 305.1 and were assumed to have ceased smoking during hospital stay. Patients who developed acute gout inhospital were identified based on ICD-9 code 274.01 at secondary diagnosis position. Univariate and multivariate logistic regressions were used to derive odds ratio for measures of association. Statistical analysis was done using STATA version 13.0 (College Station, TX). A total of 17,847,045 discharge records were used which included 13,932 (0.08 %) inhospital acute gouty arthritis and 2,615,944 (14.66 %) active smokers. Both univariate (OR 0.59, CI 0.54-0.63, p < 0.0001) and multivariate (OR 0.64, CI 0.59-0.68, p < 0.0001) regressions showed statistically significant reduction of acute gout among hospitalized patients who were current smokers but were assumed to have ceased smoking during hospital stay. Active tobacco use was associated with a lower risk of acute inpatient gouty arthritis, even when controlling for conventional risk factors. More study is needed to correlate this finding with uric acid levels, and a better understanding of the mechanisms that explain this finding are necessary.