Association of Visceral Adipose Tissue with Gout: Observational and Mendelian Randomization Analyses
Gout, a form of inflammatory arthritis, is a significant public health concern worldwide, with prevalence rates ranging from 0.68% to 3.90% among adults. The Global Burden of Disease 2017 study highlights the substantial impact of gout, reporting approximately 41.2 million prevalent cases, 7.4 million incident cases annually, and nearly 1.3 million years lived with disability due to the condition. Beyond its direct effects, gout is associated with increased risks of cardiovascular disease, diabetes mellitus, Alzheimer’s disease, and all-cause mortality. Given the heavy burden of gout, identifying modifiable risk factors is crucial for developing effective prevention strategies. Among the potential risk factors, adiposity, particularly visceral adipose tissue (VAT), has emerged as a promising target for intervention.
Previous studies have established a link between body mass index (BMI) and the risk of gout. However, BMI is an indirect measure that does not differentiate between fat and lean body mass or indicate the location of adipose tissue. Central adiposity, primarily referring to VAT, represents increased ectopic fat deposits in metabolically important organs and has been causally associated with adverse outcomes such as cancers, cardiovascular disease, and all-cause mortality. Despite these findings, the causal relationship between VAT and gout remains unclear. This study aims to address this gap by examining the association between VAT and gout using both observational and Mendelian randomization (MR) analyses.
The study utilized data from the National Health and Nutrition Examination Survey (NHANES) for observational analyses and summary data from genome-wide association studies (GWAS) for MR analyses. The NHANES dataset included 11,967 participants aged 39.5 ± 11.5 years, of whom 295 (2.47%) were identified as having gout. VAT mass was measured using dual-energy X-ray absorptiometry (DXA), and gout was assessed through self-reported diagnoses. Covariates included sociodemographic information, lifestyle behaviors, laboratory data, and clinical characteristics such as hypertension, diabetes, chronic kidney disease (CKD), coronary heart disease (CHD), and stroke.
In the observational analyses, logistic regression models were used to investigate the association between VAT mass and the risk of gout. The results showed that each standard deviation (SD) increase in VAT mass was associated with a higher risk of gout, with an odds ratio (OR) of 1.27 (95% confidence interval [CI] = 1.11–1.45) after adjusting for confounding factors. When VAT mass was categorized into quartiles, participants in the highest quartile (Q4) had a significantly higher risk of gout compared to those in the lowest quartile (Q1), with an OR of 2.73 (95% CI = 1.16–6.45) in the fully adjusted model. These findings suggest a robust association between increased VAT mass and the risk of gout.
To further explore the causal relationship between VAT and gout, the study conducted two-sample MR analyses using genetic variants associated with VAT mass as instrumental variables (IVs). The MR analyses included 211 single-nucleotide polymorphisms (SNPs) derived from GWAS data on VAT mass from the UK Biobank and summary data on gout from the Chronic Kidney Disease Genetics (CKDGen) Consortium. The primary analysis used the inverse-variance weighted (IVW) method, which demonstrated a causal association between increased VAT mass and the risk of gout, with an OR of 1.78 (95% CI = 1.57–2.03). Sensitivity analyses, including MR-Egger, weighted median, simple mode, and weighted mode, confirmed the robustness of these findings. The MR-Egger intercept test indicated no significant evidence of horizontal pleiotropy, and leave-one-out analyses showed that no single SNP drove the observed associations.
The study’s findings are consistent with previous research linking adiposity to gout. For instance, a meta-analysis by Aune et al. reported that each 5-unit increase in BMI was associated with a 55% higher risk of gout. Similarly, Larsson et al. used MR analyses to demonstrate a causal effect of BMI on gout risk. However, this study is the first to specifically investigate the role of VAT in gout risk using both observational and MR methods. The results suggest that VAT, as a measure of central adiposity, may have a more direct and independent association with gout compared to BMI.
The potential mechanisms underlying the association between VAT and gout are not fully understood but may involve inflammation. VAT is known to secrete inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin-1 (IL-1), IL-27, and IL-6, which play important roles in the development of gout. These inflammatory markers may contribute to the pathogenesis of gout by promoting the production and deposition of urate crystals, leading to acute inflammatory responses.
The study has several strengths, including the use of a nationally representative sample from NHANES and the application of MR analyses to establish causality. The significant association between VAT mass and gout persisted after adjusting for BMI, uric acid (UA), and subcutaneous fat mass (SAF), emphasizing the independent role of VAT in gout risk. However, there are limitations to consider. VAT mass was measured using DXA, which may introduce bias compared to the gold-standard method. Additionally, gout diagnoses were based on self-reported data, which may be subject to recall bias and misclassification. Finally, the study did not investigate the underlying mechanisms of the association between VAT and gout, warranting further research.
In conclusion, this study provides robust evidence of an association between increased VAT mass and the risk of gout, supported by both observational and MR analyses. The findings suggest that targeted interventions to reduce VAT mass may be beneficial in preventing or ameliorating gout. Future research should explore the mechanisms underlying this association and evaluate the effectiveness of interventions aimed at reducing VAT mass in gout prevention.
doi.org/10.1097/CM9.0000000000002908
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