Body Mass Index and the Risk of Rheumatic Disease: Linear and Nonlinear Mendelian Randomization Analyses

Abstract

ObjectiveWhile the association between obesity and risk of rheumatic disease is well established, the precise causal relation has not been conclusively proved. Here, we estimate the causal effect of body mass index (BMI) on the risk of developing five different rheumatic diseases.MethodsLinear and nonlinear mendelian randomization (MR) were used to estimate the effect of BMI on risk of rheumatic disease, and sex‐specific effects were identified. Analyses were performed in 361,952 participants from the UK Biobank cohort for the five rheumatic diseases: rheumatoid arthritis (N=8,381 cases), osteoarthritis (N=87,430), psoriatic arthropathy (N=933), gout (N=13,638), and inflammatory spondylitis (N=4,328).ResultsUsing linear MR, we found that one standard deviation higher BMI increases the incidence rate for rheumatoid arthritis (IRR=1.52; 95% CI=1.36‐1.69), osteoarthritis (IRR=1.49; 1.43‐1.55), psoriatic arthropathy (IRR=1.80; 1.31‐2.48), gout (IRR=1.73; 1.56‐1.92), and inflammatory spondylitis (IRR=1.34; 1.14‐1.57) in all individuals. BMI was found to be a stronger risk factor in women compared to men for psoriatic arthropathy (sex‐interaction P=3.3×10‐4) and gout (P=4.3×10‐3), and the effect on osteoarthritis was stronger in premenopausal compared to postmenopausal women (P=1.8×10‐3). Nonlinear effects of BMI were identified for osteoarthritis and gout in men, and for gout in women. The nonlinearity for gout was also more extreme in men compared to women (P=0.03).ConclusionHigher BMI causes an increased risk for rheumatic disease, an effect that is more pronounced in women for both gout and psoriatic arthropathy. The novel sex‐ and BMI‐specific causal effects identified here, give further insight into rheumatic‐disease etiology and mark an important step towards personalized medicine.This article is protected by copyright. All rights reserved.

Phenome-wide causal associations between osteoarthritis and other complex traits through the latent causal variable analysis

“…Previous literature has robustly documented the associations between OA and multiple anthropometric parameters. The causative roles of these factors have been corroborated through MR studies, highlighting variables such as BMI ( [ 9 , 10 , 22 – 25 ], obesity [ 26 ], body weight [ 9 ], hip circumference [ 9 , 10 ], waist circumference [ 9 , 10 ], and BMD [ 27 – 29 ]. This current analysis further substantiated these causal relationships via the LCV methodology.…”

Exploring the Two-Way Link between Migraines and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study

“…For achieving credible estimations of Mendelian Randomization causality, efficacious genetic variances serving as IVs must meet three central postulates: (I) Relevance Assumption, asserting that variations must demonstrate intimate association with the exposure element; (II) Independence/Exchangeability Assumption, demanding no correlations be exhibited with any measured, unmeasured, or inconspicuous confounding elements germane to the researched correlation of interest; and (III) Exclusion Restriction Assumption, maintaining that the variation affects the outcome exclusively through the exposure, devoid of alternative routes. 10,11 This article is protected by copyright. All rights reserved.…”

“…Lastly, as our Mendelian Randomization analysis relies on publicly available summary statistics data, the lack of detailed clinical information hinders subgroup analysis. 10 This article is protected by copyright. All rights reserved.…”

Association between total protein, albumin, globulin, albumin- globulin ratio and rheumatoid arthritis: evidence from NHANES and Mendelian randomization

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