| Title: | Re-analysis and meta-analysis of summary statistics from gene-environment interaction studies |
| Journal: | Bioinformatics |
| Published: | 1 Dec 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38039147/ |
| DOI: | https://doi.org/10.1093/bioinformatics/btad730 |
| URL: | https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btad730/53970809/btad730.pdf |
Publication 8227
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Abstract
MOTIVATION: 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, there is a need for gene-environment interaction-specific methods that manipulate and use summary statistics.</p>
RESULTS: 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 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 multiple exposures from multiple studies. We demonstrate the value and efficiency of these tools by exploring alternative methods of accounting for ancestry-related population stratification in genome-wide interaction study in the UK Biobank as well as by conducting a multi-exposure genome-wide interaction study meta-analysis in cohorts from the diabetes-focused ProDiGY consortium. These programs help to maximize the value of summary statistics from diverse and complex gene-environment interaction studies.</p>
AVAILABILITY AND IMPLEMENTATION: REGEM and METAGEM are open-source projects freely available at https://github.com/large-scale-gxe-methods/REGEM and https://github.com/large-scale-gxe-methods/METAGEM.</p>
15 Authors
- Duy T Pham
- Kenneth E Westerman
- Cong Pan
- Ling Chen
- Shylaja Srinivasan
- Elvira Isganaitis
- Mary Ellen Vajravelu
- Fida Bacha
- Steve Chernausek
- Rose Gubitosi-Klug
- Jasmin Divers
- Catherine Pihoker
- Santica M Marcovina
- Alisa K Manning
- Han Chen
Enabling scientific discoveries that improve human health