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Objective: To investigate the association between obesity-related traits and risk of rheumatoid arthritis (RA)., Methods: We conducted genetic correlation analysis and a 2-sample Mendelian randomization (MR) study, using genome-wide genetic data based on >850,000 individuals of European ancestry. Summary statistics were collected from the largest genome-wide association study conducted to date for body mass index (BMI; n = 806,810), waist-to-hip ratio (WHR; n = 697,734), WHR adjusted for BMI (WHRadjBMI; n = 694,649), and RA (n case = 14,361, n control = 43,923). We conducted cross-trait linkage disequilibrium score regression and ρ-HESS analyses to quantify genetic correlation between pairs of traits (causal overlap). For each obesity-related exposure, we utilized independent, genome-wide significant single-nucleotide polymorphisms (P < 5 × 10 -9 ) as instruments to perform MR analysis (causal relationship). We interrogated the causal relationship both in the general population and in a sex-specific manner and calculated odds ratios (ORs) and 95% confidence intervals (95% CIs). Sensitivity analyses were performed to validate MR model assumptions., Results: Despite a negligible overall genetic correlation between the 3 obesity-related traits and RA, we found significant local genetic correlations at several regions on chromosome 6 (positions 28-29M, 30-35M, and 50-52M), highlighting a shared genetic basis. We further observed an increased risk of RA per SD increment (4.8 kg/m 2 ) in genetically predicted BMI (OR 1.22 [95% CI 1.09-1.37]). The effect was consistent across sensitivity analyses and comparable between sexes (OR 1.22 [95% CI 1.04-1.44] in male subjects and 1.19 [95% CI 1.04-1.36] in female subjects). However, we did not find evidence supporting a causal role of either WHR (OR 0.98 [95% CI 0.84-1.14]) or WHRadjBMI (OR 0.90 [95% CI 0.79-1.04]) in RA., Conclusion: Genetically predicted BMI significantly increases RA risk. Future studies are needed to understand the biologic mechanisms underlying this link., (© 2020 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Antihypertensive, lipid‐lowering, and blood glucose‐lowering drugs have slowed down the aging process in animal models. In humans, studies are limited, have short follow‐up times, and show mixed results. Therefore, this study aimed to estimate the effects of commonly used medications on functional aging, cognitive function, and frailty. We included information on individuals from three Swedish longitudinal population‐based studies collected between 1986 and 2014. Our exposures were the 21 most used groups of medications among individuals aged 65 years and older in the Swedish population in 2022. Functional aging index (n = 1191), cognitive function (n = 1094), and frailty index (n = 1361) were the outcomes of interest. To estimate the medication effects, we used a self‐controlled analysis, where each individual is his/her own control, thereby adjusting for all time‐stable confounders. The analysis was additionally adjusted for time‐varying confounders (chronological age, Charlson Comorbidity Index, smoking, body mass index, and the number of drugs). The participants were 65.5–82.8 years at the first in‐person assessment. Adrenergics/inhalants (effect size = 0.089) and lipid‐modifying agents/plain (effect size = 0.082) were associated with higher values of cognitive function (improvement), and selective calcium channel blockers with mainly vascular effects (effect size = −0.129) were associated with lower values of the functional aging index (improvement). No beneficial effects were found on the frailty index. Adrenergics/inhalants, lipid‐modifying agents/plain, and selective calcium channel blockers with mainly vascular effects may benefit functional biomarkers of aging. More research is needed to investigate their clinical value in preventing adverse aging outcomes. [ABSTRACT FROM AUTHOR]