Estimation of the Causal Relationship Between BMI and Osteoarthritis

After data from the GWAS study or GWAS meta-analysis associated with BMI or osteoarthritis were obtained via MR-Base platform,¹² MR analysis was further carried out using the package “TwoSampleMR” of the R program (version 3.4.2). Three statistical methods including inverse-variance weighted (IVW) method, weighted median estimator, and MR-Egger regression were used to investigate the causal relationship between BMI and osteoarthritis.^12–15 The IVW method is the method to assess the causal relationship by the meta-analysis of every Wald ratio for the included SNPs.^12,13 Significantly, there is a premise for the IVW method that all the included SNPs must be valid variables. Unlike the IVW method, the MR-Egger regression can still function when all the SNPs are invalid.¹⁵ The slope of MR-Egger indicates the effect of BMI on osteoarthritis when the intercept term is zero or without statistical significance.^12,15 The weighted median estimator was intermediate and the valid variables must be no less than 50%.¹⁴ The result of the weighted median estimator was the median when the effect estimations of each single SNP are sorted in the order of weight values. The estimation of the causal relationship between BMI and osteoarthritis was expressed as odds ratio (OR) and its 95% confidence interval (CI). A P value less than 0.05 indicates that the difference is statistically significant.