%0 Journal Article
%T Discovering non-additive heritability using additive GWAS summary statistics.
%A Pattillo Smith S
%A Darnell G
%A Udwin D
%A Stamp J
%A Harpak A
%A Ramachandran S
%A Crawford L
%J Elife
%V 13
%N 0
%D 2024 Jun 24
%M 38913556
%F 8.713
%R 10.7554/eLife.90459
%X 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.