| Title: | Identifying latent genetic interactions in genome-wide association studies using multiple traits |
| Journal: | Genome Medicine |
| Published: | 25 Apr 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38664839/ |
| DOI: | https://doi.org/10.1186/s13073-024-01329-0 |
| URL: | http://dx.doi.org/10.1186/s13073-024-01329-0 |
Publication 9839
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Abstract
The "missing" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods. We then apply LIT to obesity-related traits in the UK Biobank and detect variants with interactive effects near known obesity-related genes (URL: https://CRAN.R-project.org/package=lit).</p>
6 Authors
- Andrew J. Bass
- Shijia Bian
- Aliza P. Wingo
- Thomas S. Wingo
- David J. Cutler
- Michael P. Epstein
1 Application
| Application ID | Title |
|---|---|
| 58259 | Multi-omics analyses of psychiatric and neurological disorders |
Enabling scientific discoveries that improve human health