| Title: | Discovering non-additive heritability using additive GWAS summary statistics |
| Journal: | eLife |
| Published: | 24 Jun 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38913556/ |
| DOI: | https://doi.org/10.7554/elife.90459 |
Publication 11801
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Abstract
LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.</p>
10 Keywords
- Biological Specimen Banks
- Genetic Variation
- Genome-Wide Association Study
- Humans
- Japan
- Models, Genetic
- Multifactorial Inheritance
- Phenotype
- Polymorphism, Single Nucleotide
- United Kingdom
7 Authors
- Samuel Pattillo Smith
- Gregory Darnell
- Dana Udwin
- Julian Stamp
- Arbel Harpak
- Sohini Ramachandran
- Lorin Crawford
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