Summary statistics from large-scale gene-environment interaction studies for re-analysis and meta-analysis

Summary statistics from genome-wide association studies enable many valuable downstream analyses that are more efficient than individual-level data analysis while also reducing privacy concerns. As growing sample sizes enable better-powered analysis of gene-environment interactions (GEIs), there is a need for GEI-specific methods that manipulate and use summary statistics. We introduce two tools to facilitate such analysis, with a focus on statistical models containing multiple gene-exposure and/or gene-covariate interaction terms. REGEM (RE-analysis of GEM summary statistics) uses summary statistics from a single, multi-exposure genome-wide interaction study (GWIS) to derive analogous sets of summary statistics with arbitrary sets of exposures and interaction covariate adjustments. METAGEM (META-analysis of GEM summary statistics) extends current fixed-effects meta-analysis models to incorporate more complex statistical models. We demonstrate the value and efficiency of these tools by exploring alternative methods of accounting for ancestry-related population stratification in GWIS in the UK Biobank. These programs help to maximize the value of summary statistics from diverse and complex GEI studies. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by NIH grant R01 HL145025. KEW was funded by NIH grant K01 DK133637. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB of The University of Texas Health Science Center at Houston (UTHealth) gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The individual-level data that support the findings of this study are available upon application to the UK Biobank (https:/www.ukbiobank.ac.uk/register-apply/).