The role of lipid traits in mediating the effect of body mass index on serum urate

Association between sex hormones and gout: An analysis of the UK Biobank cohort

OBJECTIVES

To investigate the associations between sex hormones and gout.

METHODS

A total of 448,836 individuals free of gout at baseline were included from the UK Biobank. Cox regression models were used to estimate hazard ratios (HRs) for gout. Besides, we investigated the causal relationship between bioavailable testosterone (BAT) and gout using mendelian randomization (MR).

RESULTS

There were differential effects in different testosterone active states in gout. One-unit higher log-transformed total testosterone (TT) was associated with a 52 % [95 % CI, 0.39-0.58] lower risk of gout in males. In contrast, free testosterone (FT) and BAT were associated with a 74 % [95 % CI, 1.38-2.20] and a 78 % [95 % CI, 1.41-2.25] higher risk of gout in males respectively. For MR, the weighted median [OR, 1.70; 95 % CI, 1.14-2.56;] and inverse variance-weighted [OR, 1.25; 95 % CI, 0.96-1.62; P = 0.09] method revealed significant and approximately significant positive effect of genetic liability to BAT levels on the risk of gout respectively.

CONCLUSIONS

Sex hormones were potentially associated with gout. Notably, we were the first to explore different testosterone states on gout and found that FT and BAT may increase the risk of gout in males, which is opposite to TT. And the former are active states of androgens, may be more accurately reflect the association between androgens and gout.

Association between low-density lipoprotein cholesterol levels and serum uric acid to serum creatinine ratio in Chinese male gout patients

This study aimed to evaluate the association between low-density lipoprotein cholesterol (LDL-C) and serum uric acid to serum creatinine (SUA/SCr) ratio in male gout patients at different BMIs. This real-world study included 956 male gout patients aged 18-83 years. We retrospectively analyzed the medical records of Chinese male gout patients from 2017 to 2019. The correlation between LDL-C and SUA/SCr was tested after adjusting for confounding factors. We found a nonlinear relationship between LDL-C and SUA/SCr in the whole study population. Stratification analysis showed that there was actually a nonlinear relationship between LDL-C and SUA/SCr in men with a BMI of 24-28, the inflection point of LDL-C was 1.8 mmol/L, when LDL-C was greater than 1.8 mmol/L, there was a positive correlation between LDL-C levels and SUA/SCr (β = 0.67, 95% CI 0.35-0.98, P < 0.001). Moreover, LDL-C showed a significant positive correlation with SUA/SCr with a BMI of 28 or greater (β = 0.30, 95% CI 0.05-0.55, P = 0.019). However, no association was found between LDL-C and SUA/SCr with a BMI of less than 24 (β = 0.42, 95% CI - 0.03-0.86, P = 0.070). LDL-C levels were associated with SUA/SCr in Chinese male gout patients, but this correlation appeared inconsistent among different BMIs. Our findings suggest that LDL-C levels may be more noteworthy in overweight and/or obese male gout patients.

Causal relationship from heart failure to kidney function and CKD: A bidirectional two-sample mendelian randomization study

BACKGROUND

Heart Failure (HF) is a widespread condition that affects millions of people, and it is caused by issues with the heart and blood vessels. Even though we know hypertension, coronary artery disease, obesity, diabetes, and genetics can increase the risk of HF and Chronic Kidney Disease (CKD), the exact cause of these conditions remains a mystery. To bridge this gap, we adopted Mendelian Randomization (MR), which relies on genetic variants as proxies.

METHODS

We used data from European populations for our Bidirectional Two-Sample MR Study, which included 930,014 controls and 47,309 cases of HF from the HERMES consortium, as well as 736,396 controls and 51,256 cases of CKD. We also employed several MR variations, including MR-Egger, Inverse Variance Weighted (IVW), and Weighted Median Estimator (WME), to guarantee the results were accurate and comprehensive.).

RESULTS

In this study, the MR analysis found that individuals with a genetic predisposition for HF have an elevated risk of CKD. Our study revealed a significant association between the genetic prediction of HF and the risk of CKD, as evidenced by the IVW method [with an odds ratio (OR) of 1.12 (95% CI, 1.03-1.21), p = 0.009] and the WME [with an OR of 1.14 (95% CI, 1.03-1.26), p = 0.008]. This causal relationship remained robust even after conducting MR analysis while adjusting for the effects of diabetes and hypertension, yielding ORs of 1.13 (IVW:95% CI, 1.03-1.23), 1.12 (MR-Egger: 95% CI, 0.85-1.48), and 1.15 (WME:95% CI, 1.04-1.27) (p = 0.008). However, in the reverse analysis aiming to explore CKD and renal function as exposures and HF as the outcome, we did not observe a statistically significant causal link between CKD and HF.

CONCLUSION

Our study demonstrates the significance of HF in CKD progression, thus having meaningful implications for treatment and the potential for discovering new therapies. To better understand the relationship between HF and CKD, we need to conduct research in a variety of populations.

An elevated likelihood of stroke, ischemic heart disease, or heart failure in individuals with gout: a longitudinal follow-up study utilizing the National Health Information database in Korea

Objective

Accumulating evidence from other countries indicates potential associations between gout and cardiovascular diseases; however, the associations of gout with cardiovascular diseases, particularly stroke, ischemic heart disease, and heart failure, remain ambiguous in the Korean population. We hypothesized that individuals with gout are at a higher likelihood of stroke, ischemic heart disease, or heart failure. This study expands upon previous research by ensuring a comparable baseline between patient and control groups and analyzing 16 years of data derived from an extensive healthcare database.

Methods

We selected 22,480 patients with gout and 22,480 control individuals from the Korean National Health Insurance Service-Health Screening Cohort database (2002-2019), and matched them at a 1:1 ratio according to sex, age, income, and residence. A Cox proportional hazard model with weighted overlap was employed to examine the relationship between gout and the risk of stroke, ischemic heart disease, or heart failure after adjustment for several covariates.

Results

The incidences of stroke, ischemic heart disease, or heart failure in participants with gout were slightly higher than those in controls (stroke: 9.84 vs. 8.41 per 1000 person-years; ischemic heart disease: 9.77 vs. 7.15 per 1000 person-years; heart failure: 2.47 vs. 1.46 per 1000 person-years). After adjustment, the gout group had an 11% (95% confidence interval [CI] = 1.04-1.19), 28% (95% CI = 1.19-1.37), or 64% (95% CI = 1.41-1.91) higher likelihood of experiencing stroke, ischemic heart disease, or heart failure, respectively, than the control group.

Conclusion

The present findings suggest that individuals with gout in the Korean population, particularly those aged ≥ 60 years, were more likely to have stroke, ischemic heart disease, or heart failure.

Associations between serum urate and telomere length and inflammation markers: Evidence from UK Biobank cohort

Objective

Hyperuricemia and gout have become gradually more common. The effect of serum urate on organism aging and systematic inflammation is not determined. This study aims to evaluate whether serum urate is causally associated with cellular aging markers and serum inflammation markers.

Methods

A Mendelian randomization study was performed on summary-level data from the largest published genome-wide association studies. Single nucleotide polymorphisms with a genome-wide significance level were selected as instrumental variables for leukocyte telomere length (LTL), and serum soluble makers of inflammation (CRP, IL-6, TNF-α, and IGF-1). Standard inverse variance weighted (IVW) method was used as the primary statistical method. The weighted median, MR-Egger regression, and MR-PRESSO methods were used for sensitivity analysis.

Results

An inverse causal association of genetically predicted serum urate levels and LTL was found using IVW method (OR: 0.96, 95%CI 0.95, 0.97; β=-0.040; SE=0.0072; P=4.37×10^-8). The association was also supported by MR results using MR-Egger method and weighted median method. The MR-PRESSO analysis and leave-one-out sensitivity analysis supported the robustness of the combined results. In terms of other aging-related serum biomarkers, there was no evidence supporting a causal effect of serum urate on CRP, IL-6, TNF-α, or IGF-1 levels.

Conclusions

Serum urate levels are negatively associated with telomere length but are not associated with serum soluble indicators of inflammation. Telomere length may be a critical marker that reflects urate-related organismal aging and may be a mechanism in the age-related pathologies and mortality caused by hyperuricemia.