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Objective: To prospectively investigate population‐based metabolomics for incident gout and reproduce the findings for recurrent flares, accounting for serum urate. Methods: We conducted a prediagnostic metabolome‐wide analysis among 105,615 UK Biobank participants with nuclear magnetic resonance metabolomic profiling data (168 total metabolites) from baseline blood samples collected 2006–2010 in those without history of gout. We calculated hazard ratios (HRs) for incident gout, adjusted for gout risk factors, excluding and including serum urate levels, overall and according to fasting duration before sample collection. Potential causal effects were tested with 2‐sample Mendelian randomization. Poisson regression was used to calculate rate ratios (RRs) for the association with recurrent flares among incident gout cases. Results: Correcting for multiple testing, 88 metabolites were associated with risk of incident gout (N = 1,303 cases) before serum urate adjustment, including glutamine and glycine (inversely), and lipids, branched‐chain amino acids, and most prominently, glycoprotein acetyls (GlycA; P = 9.17 × 10−32). Only GlycA remained associated with incident gout following urate adjustment (HR 1.52 [95% confidence interval (95% CI) 1.22–1.88] between extreme quintiles); the HR increased progressively with fasting duration before sample collection, reaching 4.01 (95% CI 1.36–11.82) for ≥8 hours of fasting. Corresponding HRs per SD change in GlycA levels were 1.10 (95% CI 1.04–1.17) overall and 1.54 (95% CI 1.21–1.96) for ≥8 hours of fasting. GlycA levels were also associated with recurrent gout flares among incident gout cases (RR 1.90 [95% CI 1.27–2.85] between extreme quintiles) with larger associations with fasting. Mendelian randomization corroborated a potential causal role for GlycA on gout risk. Conclusion: This prospective, population‐based study implicates GlycA, a stable long‐term biomarker reflecting neutrophil overactivity, in incident and recurrent gout flares (central manifestation from neutrophilic synovitis) beyond serum urate. [ABSTRACT FROM AUTHOR]

Background and purpose: We used two‐sample Mendelian randomization (MR) to examine the effects of blood lipids and lipid‐modifying drugs on intracranial aneurysm (IA). Methods: Genetic variants for the effects of high‐density lipoprotein cholesterol (HDL‐C), apolipoprotein A1, low‐density lipoprotein cholesterol (LDL‐C), apolipoprotein B, and triglycerides and targets for lipid‐modifying drugs were selected from the genome‐wide discovery analyses of the UK Biobank. Summary‐level data on IAs were obtained from the International Stroke Genetics Consortium. Univariate and multivariate MR analyses were performed. Results: Univariate MR analyses showed that the HDL‐C was negatively correlated with IA (odds ratio [OR] = 0.816, 95% confidence interval [CI] = 0.715–0.932, p = 0.003) and ruptured IA (rIA; OR = 0.775, 95% CI = 0.663–0.906, p = 0.001). The multivariate MR–inverse variance weighted analysis showed that the HDL‐C was negatively correlated with IA (OR = 0.655, 95% CI = 0.434–0.988, p = 0.043) and rIA (OR = 0.563, 95% CI = 0.347–0.913, p = 0.02), and the LDL‐C was negatively correlated with IA (OR = 0.402, 95% CI = 0.191–0.848, p = 0.017) and rIA (OR = 0.376, 95% CI = 0.160–0.883, p = 0.025). Using genetic proxies of known lipid‐modifying drugs, we found that the increased HDL‐C with cholesterol ester transfer protein proxies was associated with a decreased risk of rIA (OR = 0.852, 95% CI = 0.747–0.973, p = 0.018), and the decreased LDL‐C with 3‐hydroxy‐3‐methylglutaryl‐coenzyme A reductase proxies was associated with increased risk of IA (OR = 1.772, 95% CI = 1.080–2.908, p = 0.024) and rIA (OR = 1.856, 95% CI = 1.022–3.371, p = 0.042). Conclusions: Genetically determined HDL‐C and LDL‐C reduce the risk of IA and rIA. The effects of different lipid‐modifying drugs on IA need to be further investigated. [ABSTRACT FROM AUTHOR]

Introduction: Cardiovascular disease (CVD) is the leading cause of mortality in people with Type 2 diabetes mellitus (T2DM). Statins reduce low‐density lipoproteins and positively affect CVD outcomes. Statin type and dose have differential effects on glycaemia and risk of incident T2DM; however, the impact of gender, and of individual drugs within the statin class, remains unclear. Aim: To compare effects of simvastatin and atorvastatin on lipid and glycaemic control in men and women with and without T2DM, and their association with incident T2DM. Methods: The effect of simvastatin and atorvastatin on lipid and glycaemic control was assessed in the T2DM DiaStrat cohort. Prescribed medications, gender, age, BMI, diabetes duration, blood lipid profile and HbA1c were extracted from Electronic Care Record, and compared in men and women prescribed simvastatin and atorvastatin. Analyses were replicated in the UKBiobank in those with and without T2DM. The association of simvastatin and atorvastatin with incident T2DM was also investigated in the UKBiobank. Cohorts where matched for age, BMI and diabetes duration in men and women, in the UKBioBank analysis, where possible. Results: Simvastatin was associated with better LDL (1.6 ± 0.6 vs 2.1 ± 0.9 mmol/L, p <.01) and total cholesterol (3.6 ± 0.7 vs 4.2 ± 1.0 mmol/L, p <.05), and glycaemic control (62 ± 17 vs 67 ± 19 mmol/mol, p <.059) than atorvastatin specifically in women in the DiaStrat cohort. In the UKBiobank, both men and women prescribed simvastatin had better LDL (Women: 2.6 ± 0.6 vs 2.6 ± 0.7 mmol/L, p <.05; Men: 2.4 ± 0.6 vs 2.4 ± 0.6, p <.01) and glycaemic control (Women:54 ± 14 vs 56 ± 15mmol/mol, p <.05; Men, 54 ± 14 vs 55 ± 15 mmol/mol, p <.01) than those prescribed atorvastatin. Simvastatin was also associated with reduced risk of incident T2DM in both men and women (p <.0001) in the UKBiobank. Conclusions: Simvastatin is associated with superior lipid and glycaemic control to atorvastatin in those with and without T2DM, and with fewer incident T2DM cases. Given the importance of lipid and glycaemic control in preventing secondary complications of T2DM, these findings may help inform prescribing practices. [ABSTRACT FROM AUTHOR]