To ensure independence among genetic instruments, we applied LD clumping60 with a clumping window of 10 MB and an r2 cutoff of 0.001 (default of the ld_clumpfunction)
We applied four complementary methods of two sample mendelian randomisation (inverse variance weighted method, mendelian randomisation-Egger (MR-Egger) method, weighted median method, and weighted mode based estimation), which make different assumptions about horizontal pleiotropy. A consistent effect across the four methods is less likely to be a false positive.
Two sample Mendelian randomisation (2SMR) is a method to estimate the causal effect of an exposure on an outcome using only summary statistics from genome wide association studies (GWAS).
Mendelian randomization is a method to assess the causal effect of an exposure on an outcome using an instrument, defined by one or more SNPs, as a proxy for the exposure.
Methodological advances mean that Mendelian randomization can be implemented using summary statistics from GWAS, without individual level data. This requires SNP-exposure associations and SNP-outcome associations obtained from separate datasets and is known as two-sample Mendelian randomization
ao <- available_outcomes()
exposure_dat <- extract_instruments(c('ukb-a-360'))
outcome_dat <- extract_outcome_data(exposure_dat$SNP, c('7'),
proxies = 1, rsq = 0.8, align_alleles = 1,
palindromes = 1, maf_threshold = 0.3)
dat <- harmonise_data(exposure_dat, outcome_dat, action = 2)
mr_results <- mr(dat)
generate_odds_ratios(mr_results)
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