Assessing the causal associations of obstructive sleep apnea with serum uric acid levels and gout: a bidirectional two-sample Mendelian randomization study

OBJECTIVE

Multiple observational studies have reported the close associations of obstructive sleep apnea (OSA) with serum uric acid (SUA) levels and gout. However, the causal nature and direction remains unclear.

METHODS

A bidirectional two-sample Mendelian randomization (MR) study was performed, based on publicly available genome-wide association studies (GWAS) summary statistics, to investigate whether OSA is causally related to SUA levels, gout and vice versa. The inverse-variance weighted (IVW) was used as the primary analysis approach, supplemented with four sensitive analysis methods applied to assess the robustness of the results. Moreover, multivariable MR (MVMR) was utilized to evaluate the independent causal effect of OSA on SUA and gout after adjusting for body mass index (BMI), hypertension, type 2 diabetes (T2D), coronary artery disease (CAD), and chronic kidney disease (CKD).

RESULTS

Genetically predicted OSA liability was significantly associated with increased levels of SUA (IVW method: β = 0.19, 95% CI = 0.11 - 0.26, P = 7.24 × 10^-7) and risk of gout [IVW method: odds ratio (OR) = 1.75 95% CI = 1.13 - 2.69, P = 0.01] in univariable MR. The MVMR results suggested that OSA retained its significant association with increased SUA levels, whereas the significant association between OSA and gout was attenuated to null after adjusting for BMI and T2D. No causal effect of OSA on SUA levels and gout was found in the reverse direction.

CONCLUSIONS

Our findings suggest that OSA was causally associated with increased levels of SUA, but was not independently associated with gout risk.

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.

Confounded by obesity and modulated by urinary uric acid excretion, sleep-disordered breathing indirectly relates to hyperuricaemia in males: A structural equation model

Sleep-disordered breathing (SDB) causes hypoxic stress and can trigger uric acid (UA) overproduction. We comprehensively investigated whether SDB, interacting with components of metabolic syndrome, hepatic and renal dysfunctions, low physical fitness, sedentary lifestyle, disrupted sleep, and chronic systemic inflammation (CSI), is directly associated with hyperuricaemia. In 528 community-based males (mean [SD] age 46.2 [7.4] years), we cross-sectionally analysed measures of anthropometry; self-reported lifestyle habits; overnight sleep polysomnography data; cardiopulmonary exercise tests; and biomarkers of cardiometabolic, hepatic, and renal functions; and CSI, using structural equation modelling. Objective disrupted sleep, C-reactive protein, low physical fitness, and sedentary lifestyle were not related to UA levels in univariate analysis and were excluded. The latent variables (with corresponding manifest variables) obesity (body mass index, waist-hip ratio), hypertension (post-sleep systolic, diastolic blood pressure), dyslipidaemia (total cholesterol, triglyceride/high-density lipoprotein cholesterol), hepatic dysfunction (alanine aminotransferase, aspartate transaminase), and renal dysfunction (blood urea nitrogen, serum creatinine) were positively; and hyperglycaemia (fasting glucose, glycated haemoglobin) was negatively associated with hyperuricaemia (serum UA), except for SDB (Apnea-Hypopnea Index, percentage of oxygen saturation <90% period against total sleep time, oxygen desaturation index) in the one-stage influence model. In the two-stage model, SDB, closely interacting with obesity, was positively indirectly associated with hyperuricaemia through directly linked renal dysfunction and obesity-linked hypertension, inverse hyperglycaemia, dyslipidaemia, and hepatic dysfunction. In conclusion, structural equation modelling reveals that SDB closely interacts with obesity and is positively but indirectly related to hyperuricaemia in males. This suggests that urinary UA excretion modulates and obesity confounds the SDB-hyperuricaemia relationship.

Does Continuous Positive Airway Pressure Therapy in Patients with Obstructive Sleep Apnea Improves Uric Acid? A Meta-Analysis

Purpose

The efficacy of obstructive sleep apnea (OSA) therapy with continuous positive airway pressure (CPAP) on uric acid (UA) yielded conflicting results. This meta-analysis was performed to assess whether OSA treatment with CPAP could reduce UA levels.

Methods

The Web of Science, Cochrane Library, Embase, and PubMed were searched before March 2019. Information of patients, study design, and pre- and post-CPAP treatment of UA was utilized for analysis. The overall effects were analyzed via the standardized mean difference (SMD) with a 95% confidence interval (CI). Five studies were obtained and the meta-analysis was performed using Stata 12.0 and Review Manager 5.2.

Results

A total of 5 studies with 6 cohorts (2 RCT and 3 observational studies) involving 270 patients were pooled into meta-analysis. There was no change of UA levels before and after CPAP treatment in OSA patients (SMD = ‐0.20, 95% CI: -0.78 to 0.37, Z = 0.69, p = 0.49). Subgroup analysis showed that the outcomes were not affected by age of patients, gender distribution, baseline body mass index, daily duration, duration of CPAP treatment, sample size, and study design.

Conclusions

This meta-analysis revealed that CPAP treatment has no effect on UA in OSA patients. Further well-designed, large-scale randomized controlled trials are required to address this issue.

The Risk of Gout Among Patients With Sleep Apnea: A Matched Cohort Study

OBJECTIVE

Obstructive sleep apnea (OSA) is associated with a range of serious comorbidities. This study was undertaken to investigate whether people with OSA are more likely to develop gout, in the short and long term, compared to those without OSA.

METHODS

A matched retrospective cohort study was undertaken using the UK Clinical Practice Research Datalink. Individuals age ≥18 years who received a diagnosis of OSA between 1990 and 2010 were identified and matched on age, sex, and practice with up to 4 individuals without OSA; follow-up was until the end of 2015. Hazard ratios (HRs) were estimated using Cox regression adjusted for general health, lifestyle, and comorbidity characteristics. The risk of developing gout was assessed at different time points, and the body mass index (BMI) category-specific results were presented.

RESULTS

The study sample included 15,879 patients with OSA and 63,296 without. The median follow-up was 5.8 years. We found that 4.9% of patients with OSA and 2.6% of patients without the disorder developed gout. The incidence rate per 1,000 person-years was 7.83 (95% confidence interval [95% CI] 7.29-8.40) and 4.03 (95% CI 3.84-4.23) among those with and without OSA, respectively. The adjusted HR was 1.42 (95% CI 1.29-1.56). The risk of developing gout among OSA patients compared to those without was highest 1-2 years after the index date (HR 1.64 [95% CI 1.30-2.06]). This finding persisted among those who were overweight and obese. For those with normal BMI, the highest significant HR (2.02 [95% CI 1.13-3.62]) was observed at 2-5 years after the index date.

CONCLUSION

In this study, patients with OSA continued to be at higher risk of developing gout beyond the first year following the diagnosis. Our results further indicate that peak incidences of gout vary according to BMI.

Continuous Positive Airway Pressure Treatment Does not Reduce Uric Acid Levels in OSA Women

OBJECTIVES

Although an association between uric acid (UA) levels and obstructive sleep apnea (OSA) has been reported, the effect of continuous positive airway pressure (CPAP) on this measure is yet unclear. We aimed to investigate the effect of CPAP therapy on serum UA levels in patients with OSA.

METHODS

We conducted a multicenter, open-label, randomized controlled trial in 307 women diagnosed with moderate-to-severe OSA (apnea-hypopnea index [AHI]≥15) in 19 Spanish Sleep Units. Women were randomized to CPAP (n=151) or conservative treatment (n=156) for 12 weeks. Changes in serum UA measures were assessed on an intention-to-treat basis. Additional analyses were conducted in the subgroup of women with CPAP adherence ≥4h/night and those with UA levels ≥6mg/dl.

RESULTS

Women had a mean (SD) age of 57.1 (10.1) years, median (first-third quartile) body mass index of 33.7 (29.0-38.5) mg/kg² and AHI of 32.0 (22.6-48.5). The average serum UA measure was 5.11 (1.26) mg/dl, and 80 (26.1%) participants had UA≥6mg/dl. Compared with the control group, the CPAP group did not achieve any reduction in UA levels (non-adjusted intergroup difference -0.03mg/dl, 95%CI -0.20 to 0.13; p=0.702) after 12 weeks of follow-up. These results did not change when the analysis was restricted to women with CPAP adherence ≥4h/night, or the subgroup of women with hyperuricemia.

CONCLUSIONS

Twelve weeks of CPAP therapy does not reduce UA levels compared to conservative treatment in women with moderate-to-severe OSA.

Periodontal Status in Morbidly Obese Patients With and Without Obstructive Sleep Apnea Syndrome Risk: A Cross-Sectional Study

BACKGROUND

This cross-sectional study aims to investigate the correlation between obstructive sleep apnea syndrome (OSAS) risk with periodontal disease and anthropometric measures in Class III obese patients.

METHODS

Anthropometric measurements were taken from 108 patients of both sexes, aged 30 to 60 years. The Berlin questionnaire (Bq) and the Epworth sleepiness scale (ESS) were applied to determine the risk for OSAS. Full-mouth periodontal status was determined by probing depth, clinical attachment level, gingival bleeding index, and the presence of calculus. Unpaired Student t, χ(2), Fisher exact, and Mann-Whitney U tests were applied to analyze the differences between high and low risk for OSAS groups.

RESULTS

Overall, 81.5% of the patients showed high risk for OSAS, 46.3% had excessive daytime sleepiness, 41.5% were positive for both the Bq and ESS, and 97.2% had periodontal disease (periodontitis = 85.2% and gingivitis = 60.2%). Patients with periodontal disease showed high risk for OSAS (82.9%) and ESS (45.7%). However, there was no influence of periodontal disease on OSAS risk. Periodontitis was not associated with the ESS (odds ratio [OR] = 1.84, 95% confidence interval [CI] = 0.54 to 6.26) or Bq (OR = 0.87, 95% CI = 0.10 to 7.84), nor was gingivitis associated with the ESS (OR = 1.25, 95% CI = 0.48 to 3.25) or Bq (OR = 0.23, 95% CI = 0.03 to 1.84). Waist circumference (P = 0.03), neck circumference (NC, P <0.001), and the percentage of predicted NC (PPNC, P <0.001) were significantly larger in the patients at high risk for OSAS than in those at low risk for OSAS. Daytime sleepiness was also associated with NC (P = 0.02) and PPNC (P = 0.02).

CONCLUSION

There was no association between periodontal disease and OSAS risk in Class III obese patients, but OSAS risk was associated with both NC and PPNC.