Separate GWAS were conducted at each developmental period for each available sample with linear regression using PLINK (Purcell et al. 2007) in unrelated participants (ALSPAC). We conducted GWAS with a linear mixed model with a genomic relatedness matrix (GRM) using Genome-wide Complex Trait Analysis (GCTA; Yang et al. 2011) in COGA and Add Health to adjust the standard error of SNP effect sizes for non-independence of observations among participants that are biological relatives. GRMs were constructed in each sample (COGA, Add Health) using GCTA. SNPs were pruned for GRM calculation using a 50 SNP window, shifting by 5 SNPs, with a variance inflation factor threshold of 2 in PLINK. GWAS summary statistics were meta-analyzed within developmental periods using an inverse variance-weighted meta-analysis in METAL (Willer et al. 2010).
