Sang-Cheol Bae1, Young Ho Lee2. 1. Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea. 2. Department of Rheumatology, Korea University College of Medicine, Seoul, Korea.
Abstract
OBJECTIVE: This study aimed to examine whether body mass index (BMI) is causally associated with rheumatoid arthritis (RA). METHOD: A two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) meta-analyses for BMI in individuals of European descent (n = 322 154; GIANT consortium) as the exposure and a GWAS for noncancer illness code self-reported: RA from the individuals included in the UK Biobank (total n = 337 159; case = 7480, control = 329 679) as the outcome. RESULTS: We selected 68 single nucleotide polymorphisms at genome-wide significance from GWASs on BMI as the instrumental variables. The IVW method showed evidence to support a causal association between BMI and RA (beta = 0.003, SE = 0.001, P = 0.033). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = -3.54E-05; P = 0.736), but it showed no causal association between BMI and RA (beta = 0.004, SE = 0.004, P = 0.302). However, the weighted median approach yielded evidence of a causal association between BMI and RA (beta = 0.006, SE = 0.002, P = 0.004). Cochran's Q test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy. CONCLUSION: The results of MR analysis support that BMI may be causally associated with an increased risk of RA.
OBJECTIVE: This study aimed to examine whether body mass index (BMI) is causally associated with rheumatoid arthritis (RA). METHOD: A two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) meta-analyses for BMI in individuals of European descent (n = 322 154; GIANT consortium) as the exposure and a GWAS for noncancer illness code self-reported: RA from the individuals included in the UK Biobank (total n = 337 159; case = 7480, control = 329 679) as the outcome. RESULTS: We selected 68 single nucleotide polymorphisms at genome-wide significance from GWASs on BMI as the instrumental variables. The IVW method showed evidence to support a causal association between BMI and RA (beta = 0.003, SE = 0.001, P = 0.033). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = -3.54E-05; P = 0.736), but it showed no causal association between BMI and RA (beta = 0.004, SE = 0.004, P = 0.302). However, the weighted median approach yielded evidence of a causal association between BMI and RA (beta = 0.006, SE = 0.002, P = 0.004). Cochran's Q test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy. CONCLUSION: The results of MR analysis support that BMI may be causally associated with an increased risk of RA.