| Title: | Buffering of gene dosage response curves for human complex traits |
| Journal: | Cell Genomics |
| Published: | 7 May 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42102804/ |
| DOI: | https://doi.org/10.1016/j.xgen.2026.101221 |
| URL: | https://www.cell.com/cell-genomics/pdf/S2666-979X(26)00083-2.pdf |
Publication 20147
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Abstract
The genome-wide burdens of deletions, loss-of-function mutations, and duplications correlate with many traits. Curiously, for most of these traits, variants that decrease expression have the same genome-wide average direction of effect as variants that increase expression. This seemingly contradicts the intuition that for individual genes, reducing expression should have the opposite effect on a phenotype as increasing expression. To understand this paradox, we use the gene dosage response curve (GDRC), which relates changes in gene expression to expected changes in phenotype. We show that, for many traits, GDRCs are systematically biased in one trait direction relative to the other, a phenomenon we call trait buffering. Because of trait buffering, traits are more easily modified in one direction than the other by genetic variation. We develop a simple theoretical model that explains this bias in trait direction. Our results have broad implications for complex traits, drug discovery, and statistical genetics.</p>
6 Authors
- Nikhil Milind
- Courtney J Smith
- Huisheng Zhu
- Tamara Gjorgjieva
- Jeffrey P Spence
- Jonathan K Pritchard
1 Application
| Application ID | Title |
|---|---|
| 30418 | Biomarker profiling by NMR metabolomics for the study of chronic disease risk and underlying risk factors |
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