Compiling MR-Base Genetic Datasets

We downloaded publicly available datasets from study-specific websites and dbGAP and invited studies curated by the NHGRI-EBI GWAS catalog to share results (if these were not already publically available). To be eligible for inclusion in MR-Base, studies should provide the following information for each SNP: the beta coefficient and standard error from a regression model (typically an additive model) and the modelled effect and non-effect alleles. This is the minimum information required for implementation of 2SMR. The following information is also sought but is not essential: effect allele frequency, sample size, p-values for SNP-phenotype associations, p-values for Hardy–Weinberg equilibrium, p-values for Cochran's Q test for between study heterogeneity (if a GWAS meta-analysis) and metrics of imputation quality, such as info or r² scores (for imputed SNPs). MR-Base also includes information on the following study-level characteristics: sample size, number of cases and controls (if a case-control study), standard deviation of the sample mean for continuously distributed traits, geographic origin and whether the GWAS was conducted in males or females (or both). In future extensions to MR-Base, we plan to collate more detailed information on phenotype distributions (e.g. sample means for continuously distributed phenotypes) and population characteristics (mean and standard deviation of age and number of males and females) and statistical models (e.g. covariates included in regression models and genomic control inflation factors).