Genomic summary statistics and meta-analysis for set-based gene-environment interaction tests in large-scale sequencing studies

We propose an efficient method to generate the summary statistics for set-based gene-environment interaction tests, as well as a meta-analysis approach that aggregates the summary statistics across different studies, which can be applied to large biobank-scale sequencing studies with related samples. Simulations showed that meta-analysis is numerically concordant with the equivalent pooled analysis using individual-level data. Moreover, meta-analysis accommodates heterogeneity between studies and enhances power in multi-ethnic studies. We applied the meta-analysis approach to the whole-exome sequencing data from the UK Biobank and successfully identified gene regions associated with waist-hip ratio, as well as those with sex-specific genetic effects.