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

Association of serum uric acid-to-high-density lipoprotein cholesterol ratio with obstructive sleep apnea: a cross-sectional study

BACKGROUND

Characterized by intermittent hypoxia (IH), sleep fragmentation, and enhanced sympathetic nervous system activity, obstructive sleep apnea (OSA) precipitates oxidative stress, systemic inflammation, and metabolic perturbations. These disturbances manifest as alterations in serum uric acid (SUA) and high-density lipoprotein cholesterol (HDL-C) levels. Recently, the ratio of SUA to HDL-C (UHR) has emerged as a potential biomarker reflecting both inflammatory and metabolic status. This study investigates the association between UHR and OSA.

METHODS

Using a cross-sectional design, data were extracted from adults aged 20 years and older in the National Health and Nutrition Examination Survey (NHANES) database, covering the period from 2015 to March 2020. OSA was determined via the NHANES Sleep Disorders Questionnaire. The investigation employed weighted logistic regression alongside trend tests to evaluate the relationship between UHR and OSA. Nonlinear relationships were examined with restricted cubic spline analysis and threshold effect analysis. Receiver operating characteristic (ROC) curves were utilized to compare the predictive capacities of UHR, SUA, and HDL-C for OSA, with the area under the curve (AUC) calculated to assess the models' predictive accuracy. In addition, mediation analyses were conducted to explore the role of body mass index (BMI) in this association, and sensitivity analyses confirmed the robustness of the findings. Subgroup analyses further assessed the impact of various covariates.

RESULTS

Among the 9985 adults included, 4906 were identified as individuals with OSA. A positive association between UHR and the risk of OSA was observed (OR = 1.02; 95% CI: 1.01, 1.04; P = 0.014). Moreover, a nonlinear relationship was confirmed (P for nonlinearity = 0.024), with an inflection point at a UHR level of 10.23. UHR demonstrated greater predictive accuracy for OSA (AUC = 0.591) compared to SUA (AUC = 0.568) and HDL-C (AUC = 0.580). Additionally, BMI was found to partially mediate the relationship between UHR and OSA, with a mediation proportion of 61.99%. This association remained significant within specific subpopulations (P < 0.05) and was further modulated by factors such as age, alcohol consumption, and diabetes status (P for interaction < 0.05). Sensitivity analyses underscored the stability of these results.

CONCLUSION

UHR is positively correlated with the risk of OSA in adults, with BMI serving as a partial mediator. The findings support UHR as a viable biomarker for early detection and risk assessment in patients with OSA. Strategies focusing on weight management may reduce the risk of OSA among individuals with elevated UHR levels.

Characteristics and clinical value of intestinal metabolites in 4 to 6-year-old children with OSAHS

OBJECTIVE

This study aims to explore the characteristics and functional changes of intestinal metabolites in children with obstructive sleep apnea hypopnea syndrome (OSAHS) aged 4-6 years old through metabolomic approaches, screen potential biomarkers and analyze their correlation with clinical indicators and preliminary discuss the roles of intestinal metabolites in the occurrence and development of OSAHS.

METHODS

We collected fecal samples from 40 OSAHS children and 40 healthy controls aged 4-6 years and recorded some OSAHS-related clinical indicators. Fecal specimens were used to detect all metabolites through untargeted metabolomics.

RESULTS

This study identified a total of 1164 intestinal metabolites and screened out 254 differential metabolites. In the OSAHS group, the relative content of 96 metabolites were higher than the control group, while the relative content of 158 metabolites were lower. The receiver operating characteristic curve analysis results showed that the area under the curve of 14 differential metabolites was greater than 0.8. The area under the curve of Formononetin is the highest, at 0.9100, with sensitivity and specificity of 82.5% and 90.0%, respectively, and is positively correlated with OAHI. The differential metabolite functions mainly include the metabolism of fatty acids and other lipid substances, cellular signaling, protein and amino acid related metabolism, disease-related functions, glucose metabolism, and vitamin metabolism.

CONCLUSION

The intestinal metabolites and metabolic function of 4-to-6-year-old children with OSAHS altered. There was a correlation between differential metabolites and clinical indicators such as uric acid, hemoglobin, and blood sugar, which has potential diagnostic value for OSAHS screening.

The causal relationship between obstructive sleep apnea and rheumatic disease: A bidirectional Mendelian randomization study

Background and Objective

Multiple studies have shown a substantial association between obstructive sleep apnea (OSA) and rheumatic disease. However, traditional studies are susceptible to confounding factors or reverse causal relationships, and the exact causal relationship still needs to be clearly defined. This study aims to use a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the causal association between OSA and rheumatoid immune diseases.

Methods

We conducted a two-sample bidirectional MR analysis by using large-scale genome-wide association studies (GWAS) summary statistics to investigate whether there is a causal relationship between OSA and rheumatic disease. Inverse variance weighted (IVW) was used as the primary analysis approach, supplemented by MR-Egger and Weighted median methods. Sensitivity analyses were conducted to ensure the robustness of the results.

Results

The MR predicted ankylosing spondylitis (AS) was associated with risk of OSA (IVW: OR = 1.0239, 95% CI = 1.0086 to 1.0394, P = 0.0021; MR-Egger: OR = 1.0374, 95% CI = 1.0089 to 1.0668, P = 0.0326; weighted median: OR = 1.0287, 95% CI = 1.0109 to 1.0467, P = 0.0014). However, no bidirectional causal association was found between other rheumatic disease and OSA. The sensitivity analysis confirmed the robustness of the results.

Conclusions

Our analysis suggests a potential causal relationship between AS and OSA. There was no direct causal relationship between OSA and other rheumatic disease. We need more experimental research on specific pathological and physiological mechanisms in the future.

Association between obstructive sleep apnea and hyperuricemia/gout in the general population: a cross-sectional study

BACKGROUND

Obstructive sleep apnea (OSA) is linked to various health conditions, including cardiovascular diseases and metabolic disorders. Hyperuricemia and gout may be associated with OSA, but large-scale studies on this are limited. This study aimed to investigate the association between hyperuricemia/gout and OSA using data from the Korea National Health and Nutrition Survey (KNHANES).

METHODS

Using the 2019-2021 KNHANES data, 11,728 participants were selected. OSA risk was assessed using the STOP-BANG questionnaire score, which is as follows: (1) high-risk (5-8), (2) intermediate-risk (3-4), and (3) low-risk (0-2). Anthropometric, socioeconomic, health-related variables, and biochemical measurements, including serum uric acid (SUA) levels, were included in the analysis. Multiple regression analyses examined the association between the STOP-BANG score and hyperuricemia/gout.

RESULTS

After assigning weights, among 25,354,276 individuals, 3,114,119 (12.2%) had a high OSA risk. The high OSA risk group exhibited higher SUA levels (5.9 mg/dL) than those of the intermediate (5.6 mg/dL) and low OSA risk groups (4.7 mg/dL) (P < 0.001). Additionally, it had a higher incidence of physician-diagnosed gout than the other groups (6.6% vs. 3.8% vs. 0.8%, respectively, P < 0.001). The STOP-BANG questionnaire scores and SUA levels were positively correlated (r = 0.383; P < 0.001). When adjusted for confounding factors, the high OSA risk group demonstrated an association with hyperuricemia (SUA ≥ 6.8 mg/d) (adjusted Odds Ratio [OR]: 1.462, 95% Confidence interval [CI]: 1.108-1.929). High and intermediate OSA risk was associated with severe hyperuricemia (SUA ≥ 9.0 mg/dL) and gout; however, the significant association between OSA and severe hyperuricemia and gout attenuated to null after adjusting for confounding factors.

CONCLUSIONS

High OSA risk was independently associated with hyperuricemia but not severe hyperuricemia or gout. Screening and management of OSA may help prevent hyperuricemia.

Gout: global epidemiology, risk factors, comorbidities and complications: a narrative review

BACKGROUND

Gout is one of the oldest known diseases and the most common form of inflammatory arthritis. The established risk factors for gout include hyperuricemia, chronic renal disease, genetic, alcohol consumption, dietary factors, diuretic use, hypertension, obesity, and metabolic syndrome. Patients with gout have an increased risk of all-cause mortality, particularly from cardiovascular disease, cancer, and infectious diseases. Gout is also associated with several complications, such as nephrolithiasis. This literature review describes the global epidemiology and trends associated with gout, before providing an overview of its risk factors and complications.

METHODS

This research used the narrative review method. Thorough searches were performed in PubMed and Google scholar, up to June 15, 2024, for articles that evaluated the risk factors, comorbidities or complications associated with gout. Moreover, we also included studies that reported the epidemiological characteristics or burden of gout at the global, regional, or national level.

RESULTS

Gout is more prevalent in developed countries, than in developing countries, although its prevalence is increasing globally. In addition, gout is much more prevalent among males than among females. Hyperuricemia has the largest role in the development of gout, although many risk factors contribute to the increasing prevalence of gout, including genes, several medications, and diet. Gout is associated with several comorbidities and complications, which need to be taken into consideration when managing gout. In recent years, gout has been found to be associated with several new comorbidities.

CONCLUSIONS

Our findings provide a comprehensive and informative overview that can be useful for the prevention, diagnosis, and management of gout.

Gout and Hyperuricemia: A Narrative Review of Their Comorbidities and Clinical Implications

Gout is the most common form of inflammatory arthritis, caused by the deposition of monosodium urate crystals in the joints due to elevated serum uric acid levels. Its prevalence and associated healthcare burden have been rising in recent decades, a trend expected to continue. It is crucial to recognize that gout and hyperuricemia are not merely causes of painful joint flares, but systemic metabolic disorders linked to a broad spectrum of comorbidities such as cardiovascular diseases, chronic kidney disease, diabetes, insulin resistance, steatotic liver disease, osteoarthritis, and respiratory and eye diseases. Numerous risk factors for gout and hyperuricemia have been identified, with recent research uncovering further associations with other conditions. To optimize patient outcomes, gout and hyperuricemia must be addressed through a holistic approach that accounts for these risk factors while providing comprehensive management of related comorbidities affecting various organ systems. This review summarizes the current knowledge on the risk factors, comorbidities, and clinical implications of gout and hyperuricemia. Future research should focus on improving patient outcomes by tailoring treatments individually and addressing the underlying metabolic comorbidities of gout with multimodal treatment.

[Characteristics and clinical value of intestinal metabolites in children aged 4-6 years with obstructive sleep apnea-hypopnea syndrome]

OBJECTIVES

To study the characteristics and clinical value of intestinal metabolites in children aged 4-6 years with obstructive sleep apnea-hypopnea syndrome (OSAHS).

METHODS

A total of 31 children aged 4-6 years with OSAHS were prospectively enrolled as the test group, and 24 healthy children aged 4-6 years were included as the control group. Relevant clinical indicators were recorded. Fecal samples were collected, and non-targeted metabolomics analysis using liquid chromatography-mass spectrometry was performed to detect all metabolites.

RESULTS

A total of 206 metabolites were detected, mainly amino acids and their derivatives. There was a significant difference in the overall composition of intestinal metabolites between the test and control groups (P<0.05). Eighteen different metabolites were selected, among which six (N-acetylmethionine, L-methionine, L-lysine, DL-phenylalanine, L-tyrosine, and L-isoleucine) had receiver operating characteristic curve areas greater than 0.7 for diagnosing OSAHS. Among them, N-acetylmethionine had the largest area under the curve, which was 0.807, with a sensitivity of 70.83% and a specificity of 80.65%. Correlation analysis between different metabolites and clinical indicators showed that there were positive correlations between the degree of tonsil enlargement and enterolactone, between uric acid and phenylacetaldehyde, between blood glucose and acetylmethionine, and between cholesterol and 9-bromodiphenyl and procaine (P<0.05). There were negative correlations between the degree of tonsil enlargement and N-methyltyramine, aspartate aminotransferase and indolepropionic acid and L-isoleucine, between alanine aminotransferase and DL-phenylalanine, between indolepropionic acid and L-isoleucine, between uric acid and hydroxyquinoline, and between urea nitrogen and N,N-dicyclohexylurea (P<0.05). The metabolic functional pathways affected by differential metabolites mainly included riboflavin metabolism, arginine and proline metabolism, pantothenic acid and coenzyme A biosynthesis, cysteine and methionine metabolism, lysine degradation and glutathione metabolism.

CONCLUSIONS

Intestinal metabolites and metabolic functions are altered in children aged 4-6 years with OSAHS, primarily involving amino acid metabolism disorders. The screened differential intestinal metabolites have potential screening and diagnostic value as biomarkers for OSAHS.

The Association of Serum Uric Acid with Risk of Obstructive Sleep Apnea: The Korean National Health and Nutrition Examination Survey 2019-2021

Upper airway collapse and apneas in obstructive sleep apnea (OSA) induce intermittent hypercapnia and hypoxia, eventually contributing to excessive uric acid production. This study aimed to evaluate the association between hyperuricemia and OSA in the general population via analysis of the eighth KNHANES dataset (2019-2021). OSA risk was identified via the STOP-Bang questionnaire, with a score ≥3 indicating high risk. Among 11,981 total participants, 4572 (38.2%) had a high OSA risk. Participants with a high OSA risk had higher uric acid levels compared to those with a low risk (5.5 ± 1.4 mg/dL vs. 4.8 ± 1.2 mg/dL, p < 0.001). Serum uric acid levels were positively correlated with STOP-Bang score (r: 0.317, p < 0.001). Multivariate analysis revealed that hyperuricemia was associated with a high OSA risk after adjusting for confounders (odds ratio: 1.30, 95%CI: 1.11-1.53, p = 0.001). Therefore, serum uric acid levels are significantly higher in those with a high OSA risk and correlate with the risk of OSA. Further, hyperuricemia is an independently associated risk factor for high OSA risk. More research is warranted to evaluate the long-term clinical outcomes of hyperuricemia in OSA and to determine whether treatment targeting hyperuricemia is effective in the clinical course of OSA.

Association of serum uric acid with all-cause and cardiovascular mortality in obstructive sleep apnea

The study investigated the association between Serum Uric Acid (SUA) levels and all-cause as well as cardiovascular mortality in patients with Obstructive Sleep Apnea (OSA). This prospective cohort study enrolled participants with OSA from four cycles of the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2008, and 2015-2018. A weighted Cox proportional hazards model was used to assess adjusted hazard ratios (aHRs) and their corresponding 95% confidence intervals (CI) for all-cause and cardiovascular mortality. Additionally, multivariable logistic regression and restricted cubic splines (RCS) models were employed to examine nonlinear relationships between SUA and all-cause and cardiovascular mortality. Among the 5,584 OSA participants included in the study, covering the four NHANES cycles and with a median follow-up of 4.333 years, a total of 537 deaths were observed, including 108 deaths attributed to cardiovascular disease. Comparing the fourth quartile (Q4) of uric acid levels, both the fifth quartile (Q5) (aHRs = 1.51, 95% CI [1.08, 2.12]) and the second quartile (Q2) (aHRs = 1.53, 95% CI [1.04, 2.25]) of uric acid levels were independently associated with an increased risk of all-cause mortality. Furthermore, comparing the fourth quartile (Q4) of uric acid levels, the second quartile (Q2) (aHRs = 2.40, 95% CI [1.08, 5.35]) of uric acid levels were independently associated with an increased risk of cardiovascular mortality. The RCS model demonstrated a U-shaped pattern in the association between SUA and all-cause mortality in OSA, with an inflection point observed at 5.83 mg/dl. The findings of this study suggest a U-shaped association between serum SUA levels and all-cause mortality and nonlinearity association between serum SUA levels and all-cause mortality. Further studies are warranted to determine the causal relationship between SUA levels and all-cause and cardiovascular mortality.

Quantitative structure-activity relationship study of amide derivatives as xanthine oxidase inhibitors using machine learning

The target of the study is to predict the inhibitory effect of amide derivatives on xanthine oxidase (XO) by building several models, which are based on the theory of the quantitative structure-activity relationship (QSAR). The heuristic method (HM) was used to linearly select descriptors and build a linear model. XGBoost was used to non-linearly select descriptors, and radial basis kernel function support vector regression (RBF SVR), polynomial kernel function SVR (poly SVR), linear kernel function SVR (linear SVR), mix-kernel function SVR (MIX SVR), and random forest (RF) were adopted to establish non-linear models, in which the MIX-SVR method gives the best result. The kernel function of MIX SVR has strong abilities of learning and generalization of established models simultaneously, which is because it is a combination of the linear kernel function, the radial basis kernel function, and the polynomial kernel function. In order to test the robustness of the models, leave-one-out cross validation (LOOCV) was adopted. In a training set, R2 = 0.97 and RMSE = 0.01; in a test set, R2 = 0.95, RMSE = 0.01, and Rcv2 = 0.96. This result is in line with the experimental expectations, which indicate that the MIX-SVR modeling approach has good applications in the study of amide derivatives.