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Author Spotlight: Implementation of BIVA for Analyzing Disease Risk Factors in Patients with Low Body Cell Mass
Published on: July 14, 2023
Causal relationship between body mass index and risk of juvenile idiopathic arthritis: A 2-sample Mendelian
Renkun Huang1, Guohua Jiang1, Jiehua Lu2
1Department of Rehabilitation Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning City, Guangxi, China.
Abstract:
The association between body mass index (BMI) and juvenile idiopathic arthritis (JIA) has been suggested, but the causal relationship remains unclear. Mendelian randomization (MR) offers a tool to address this causal question using genetic data. This study aims to investigate the causal relationship between BMI and JIA, providing genetic evidence to inform clinical prevention and treatment strategies. A total of 35 BMI-related single nucleotide polymorphisms were included as instrumental variables. Inverse variance weighting analysis revealed a significant positive association between increased BMI and higher JIA risk (odds ratio = 1.000388, 95% confidence interval: 1.000001-1.000776, P = .0494). No significant association was found in MR-Egger (P = .05154), weighted median estimator (P = .1959), or weighted models (P = .3698). The MR-Egger regression intercept was 0.019 (P = .453), indicating no significant pleiotropy, and no bias was detected in the leave-one-out sensitivity analysis or funnel plots. This study provides genetic evidence supporting a weak positive causal relationship between increased BMI and a higher risk of JIA. However, the clinical significance of this association is limited. Summary-level data were obtained from public genome-wide association studies. Single nucleotide polymorphisms associated with BMI (P < 5 × 10-8, R2 < 0.001) were selected as instrumental variables. The BMI dataset included 99,998 participants, and the JIA dataset included 15,872 participants. The primary analysis methods were inverse variance weighting, MR-Egger regression, and weighted median estimator, with additional weighted models. Sensitivity analysis was performed using the leave-one-out method, and pleiotropy was assessed using MR-Egger regression intercept. Heterogeneity was evaluated using Cochran Q test and funnel plots, and scatter plots were used to assess consistency in effect directions.
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