Association tests

Endpoint

We included 2,272 endpoints in the analysis, which consisted of 2,269 binary endpoints and 3 quantitative endpoints (HEIGHT_IRN, WEIGHT_IRN, BMI_IRN). Endpoints with less than 80 cases among the 377,277 samples were excluded, as well as endpoints labeled with an OMIT tag in the endpoint definition file.

The quantitative endpoints HEIGHT and WEIGHT were acquired from minimum phenotype data. After that, phenotype BMI was formed from them, and all of them were inverse normal transformed.

Null models

For regenie step 1 LOCO prediction computation for each endpoint, we used age, sex, 10 PCs, Finngen 1 or 2 chip or legacy genotyping batch as covariates. For sex-specific phenotypes, sample sex was left out from the covariates. We excluded covariates that had less than 10 cases.

For calculating genetic relatedness in regenie step 1, we included variants 1) imputed with an INFO score > 0.95 in all batches and 2) > 97 % non-missing genotypes and 3) MAF > 1 %. The remaining variants were LD pruned with a 1Mb window and r2 threshold of 0.1. This resulted in a set of 60,896 well-imputed not rare variants for relatedness calculation.

We used a genotype block size of 1,000 in regenie step 1.

Association tests

We ran association tests with regenie for each of the 2,272 endpoints for each variant with a minimum allele count of 5 among each phenotype’s cases and controls. We used the approximate Firth test for variants with an initial p-value of less than 0.01 and computed the standard error based on effect size and likelihood ratio test p-value (regenie options --firth --approx --pThresh 0.01 --firth-se).