Supplementary Material for: A Case Study of Fixed-Effects and Random-Effects Meta-Analysis Models for Genome-Wide Association Studies in Celiac Disease

<b><i>Background/Aims:</i></b> Amongst the many approaches to genome-wide association study (GWAS) meta-analysis (MA), the most popular methods are based on fixed-effects (FE) modeling because it tends to be the statistically most powerful approach in the absence of heterogeneity. However, FE-based MA ignores the potential heterogeneity that may exist between studies. The purpose of our analysis was to test whether results from random effects (RE)-based methods that account for heterogeneity differed significantly from the results that were originally published. <b><i>Methods:</i></b> We reanalyzed two GWAS FE-based MAs of celiac disease with RE-based methods: (1) a two-stage GWAS MA that includes 9,451 celiac disease cases and 16,434 controls from 12 collections and (2) a single-stage GWAS MA using a custom dense genotyping platform to capture low-frequency and rare variants in 12,041 cases and 12,228 controls from 7 collections. <b><i>Results:</i></b> We present evidence that SNPs at loci that were previously reported to be genome-wide significant (GWS; p &lt; 5 × 10^-8) in either the two-stage GWAS MA or the single-stage GWAS MA were not GWS when heterogeneity was accounted for by an RE MA method. <b><i>Conclusion:</i></b> This case study highlights the strengths of RE MA methods in the presence of heterogeneity and of pooled FE methods.