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Rothman’s additive interaction model based on additivity of the relative risks of two disease-risk factors has frequently been used to investigate gene–gene interactions for various traits, especially for rheumatic diseases compared with other diseases (online supplementary text). For example, a recent paper by Diaz-Gallo et al 1 reported significant additive interactions between the HLA-DRB1 shared-epitope allele and numerous non-HLA rheumatoid arthritis (RA) risk variants (eg, PTPN22 variants) in anti-citrullinated protein antibody–positive (ACPA-positive) RA.
This study investigated the validity of the additive interaction model in assessing gene–gene interactions. Genome-wide association study (GWAS) datasets including 1000 cases and 1000 controls were simulated 100 times based on an actual GWAS dataset from 2849 WTCCC2 controls (1958_British_Birth) to have European genomic features and a single variant with OR≈5, 3, 2, 1.5, 1.2 or 1 in a dominant genetic model (used in a typical additive interaction analysis). The simulated dataset is expected to have no true disease-risk effects of variants (except for an OR-simulated variant) and no true biological interaction effects between any variants on risk of a fake disease. Using the simulated datasets, all possible interactions between an OR-simulated variant and other variants in different chromosomes …
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