| Title: | Choice of phenotype scale is critical in biobank-based G × E tests |
| Journal: | Cell Genomics |
| Published: | 14 Oct 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42874583/ |
| DOI: | https://doi.org/10.1016/j.xgen.2026.101391 |
Publication 21525
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Abstract
The importance of gene-environment interactions (G × E) for complex human traits is heavily debated. Recently, biobank-based genome-wide association studies (GWASs) have revealed many statistically significant G × E signals, though most lack clear evidence of biological significance. Here, we partly explain this discrepancy by showing that many G × E signals simplify to additive effects on a different phenotype scale, a classical concern that is currently underappreciated. Our results clearly distinguish G × sex effects on height, which vanish on the log scale, from G × sex effects on testosterone, where the log scale uncovers biologically meaningful female-specific effects. Across 32 phenotypes in UK Biobank, we find that scaling by a power transformation can explain 45% of polygenic score (PGS) × sex interactions and that simple log transformation can explain 23%, with similar results for other environments. We also show that the phenotype scale can substantially impact GWAS discovery and the construction and evaluation of polygenic scores. Finally, we provide a set of guidelines to consider and choose phenotype scales in modern genetic studies.</p>
7 Authors
- Manuela Costantino
- Renée Fonseca
- Zhengtong Liu
- Zhenhong Huang
- Sriram Sankararaman
- Iain Mathieson
- Andy Dahl
1 Application
| Application ID | Title |
|---|---|
| 89052 | Developing and applying advanced statistical methods to dissect genetic and genomic heterogeneity in diverse complex traits |
Enabling scientific discoveries that improve human health